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feat(looker/tools): Enhance dashboard creation with dashboard filters (#2133)

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## Description

Enhance dashboard creation with dashboard level filters. Also improve
tool descriptions.

## PR Checklist

> Thank you for opening a Pull Request! Before submitting your PR, there
are a
> few things you can do to make sure it goes smoothly:

- [X] Make sure you reviewed

[CONTRIBUTING.md](https://github.com/googleapis/genai-toolbox/blob/main/CONTRIBUTING.md)
- [x] Make sure to open an issue as a

[bug/issue](https://github.com/googleapis/genai-toolbox/issues/new/choose)
  before writing your code! That way we can discuss the change, evaluate
  designs, and agree on the general idea
- [x] Ensure the tests and linter pass
- [x] Code coverage does not decrease (if any source code was changed)
- [x] Appropriate docs were updated (if necessary)
- [x] Make sure to add `!` if this involve a breaking change
This commit is contained in:
Dr. Strangelove
2025-12-10 16:30:20 -05:00
committed by GitHub
parent c5a6daa768
commit 285aa46b88
44 changed files with 1281 additions and 516 deletions
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1
cmd/root.go
View File

@@ -120,6 +120,7 @@ import (
_ "github.com/googleapis/genai-toolbox/internal/tools/firestore/firestorevalidaterules"
_ "github.com/googleapis/genai-toolbox/internal/tools/http"
_ "github.com/googleapis/genai-toolbox/internal/tools/looker/lookeradddashboardelement"
_ "github.com/googleapis/genai-toolbox/internal/tools/looker/lookeradddashboardfilter"
_ "github.com/googleapis/genai-toolbox/internal/tools/looker/lookerconversationalanalytics"
_ "github.com/googleapis/genai-toolbox/internal/tools/looker/lookercreateprojectfile"
_ "github.com/googleapis/genai-toolbox/internal/tools/looker/lookerdeleteprojectfile"

2
cmd/root_test.go
View File

@@ -1598,7 +1598,7 @@ func TestPrebuiltTools(t *testing.T) {
wantToolset: server.ToolsetConfigs{
"looker_tools": tools.ToolsetConfig{
Name: "looker_tools",
ToolNames: []string{"get_models", "get_explores", "get_dimensions", "get_measures", "get_filters", "get_parameters", "query", "query_sql", "query_url", "get_looks", "run_look", "make_look", "get_dashboards", "run_dashboard", "make_dashboard", "add_dashboard_element", "health_pulse", "health_analyze", "health_vacuum", "dev_mode", "get_projects", "get_project_files", "get_project_file", "create_project_file", "update_project_file", "delete_project_file", "get_connections", "get_connection_schemas", "get_connection_databases", "get_connection_tables", "get_connection_table_columns"},
ToolNames: []string{"get_models", "get_explores", "get_dimensions", "get_measures", "get_filters", "get_parameters", "query", "query_sql", "query_url", "get_looks", "run_look", "make_look", "get_dashboards", "run_dashboard", "make_dashboard", "add_dashboard_element", "add_dashboard_filter", "generate_embed_url", "health_pulse", "health_analyze", "health_vacuum", "dev_mode", "get_projects", "get_project_files", "get_project_file", "create_project_file", "update_project_file", "delete_project_file", "get_connections", "get_connection_schemas", "get_connection_databases", "get_connection_tables", "get_connection_table_columns"},
},
},
},

2
docs/en/how-to/connect-ide/looker_mcp.md
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@@ -323,6 +323,8 @@ instance and create new saved content.
data
1. **make_dashboard**: Create a saved dashboard in Looker and return the URL
1. **add_dashboard_element**: Add a tile to a dashboard
1. **add_dashboard_filter**: Add a filter to a dashboard
1. **generate_embed_url**: Generate an embed url for content
### Looker Instance Health Tools

2
docs/en/reference/prebuilt-tools.md
View File

@@ -416,6 +416,8 @@ details on how to connect your AI tools (IDEs) to databases via Toolbox and MCP.
* `run_dashboard`: Runs the queries associated with a dashboard.
* `make_dashboard`: Creates a new dashboard.
* `add_dashboard_element`: Adds a tile to a dashboard.
* `add_dashboard_filter`: Adds a filter to a dashboard.
* `generate_embed_url`: Generate an embed url for content.
* `health_pulse`: Test the health of a Looker instance.
* `health_analyze`: Analyze the LookML usage of a Looker instance.
* `health_vacuum`: Suggest LookML elements that can be removed.

29
docs/en/resources/sources/looker.md
View File

@@ -91,18 +91,17 @@ instead of hardcoding your secrets into the configuration file.
## Reference
| **field** | **type** | **required** | **description** |
|----------------------|:--------:|:------------:|-------------------------------------------------------------------------------------------|
| kind | string | true | Must be "looker". |
| base_url | string | true | The URL of your Looker server with no trailing /. |
| client_id | string | false | The client id assigned by Looker. |
| client_secret | string | false | The client secret assigned by Looker. |
| verify_ssl | string | false | Whether to check the ssl certificate of the server. |
| project | string | false | The project id to use in Google Cloud. |
| location | string | false | The location to use in Google Cloud. (default: us) |
| timeout | string | false | Maximum time to wait for query execution (e.g. "30s", "2m"). By default, 120s is applied. |
| use_client_oauth | string | false | Use OAuth tokens instead of client_id and client_secret. (default: false) If a header |
| | | | name is provided, it will be used instead of "Authorization". |
| show_hidden_models | string | false | Show or hide hidden models. (default: true) |
| show_hidden_explores | string | false | Show or hide hidden explores. (default: true) |
| show_hidden_fields | string | false | Show or hide hidden fields. (default: true) |
| **field** | **type** | **required** | **description** |
|----------------------|:--------:|:------------:|-----------------------------------------------------------------------------------------------------------------------------------------------------|
| kind | string | true | Must be "looker". |
| base_url | string | true | The URL of your Looker server with no trailing /. |
| client_id | string | false | The client id assigned by Looker. |
| client_secret | string | false | The client secret assigned by Looker. |
| verify_ssl | string | false | Whether to check the ssl certificate of the server. |
| project | string | false | The project id to use in Google Cloud. |
| location | string | false | The location to use in Google Cloud. (default: us) |
| timeout | string | false | Maximum time to wait for query execution (e.g. "30s", "2m"). By default, 120s is applied. |
| use_client_oauth | string | false | Use OAuth tokens instead of client_id and client_secret. (default: false) If a header name is provided, it will be used instead of "Authorization". |
| show_hidden_models | string | false | Show or hide hidden models. (default: true) |
| show_hidden_explores | string | false | Show or hide hidden explores. (default: true) |
| show_hidden_fields | string | false | Show or hide hidden fields. (default: true) |

62
docs/en/resources/tools/looker/looker-add-dashboard-element.md
View File

@@ -10,27 +10,18 @@ aliases:
## About
The `looker-add-dashboard-element` creates a dashboard element
in the given dashboard.
The `looker-add-dashboard-element` tool creates a new tile (element) within an existing Looker dashboard.
Tiles are added in the order this tool is called for a given `dashboard_id`.
CRITICAL ORDER OF OPERATIONS:
1. Create the dashboard using `make_dashboard`.
2. Add any dashboard-level filters using `add_dashboard_filter`.
3. Then, add elements (tiles) using this tool.
It's compatible with the following sources:
- [looker](../../sources/looker.md)
`looker-add-dashboard-element` takes eleven parameters:
1. the `model`
2. the `explore`
3. the `fields` list
4. an optional set of `filters`
5. an optional set of `pivots`
6. an optional set of `sorts`
7. an optional `limit`
8. an optional `tz`
9. an optional `vis_config`
10. the `title`
11. the `dashboard_id`
## Example
```yaml
@@ -39,24 +30,37 @@ tools:
kind: looker-add-dashboard-element
source: looker-source
description: |
add_dashboard_element Tool
This tool creates a new tile (element) within an existing Looker dashboard.
Tiles are added in the order this tool is called for a given `dashboard_id`.
This tool creates a new tile in a Looker dashboard using
the query parameters and the vis_config specified.
CRITICAL ORDER OF OPERATIONS:
1. Create the dashboard using `make_dashboard`.
2. Add any dashboard-level filters using `add_dashboard_filter`.
3. Then, add elements (tiles) using this tool.
Most of the parameters are the same as the query_url
tool. In addition, there is a title that may be provided.
The dashboard_id must be specified. That is obtained
from calling make_dashboard.
Required Parameters:
- dashboard_id: The ID of the target dashboard, obtained from `make_dashboard`.
- model_name, explore_name, fields: These query parameters are inherited
from the `query` tool and are required to define the data for the tile.
This tool can be called many times for one dashboard_id
and the resulting tiles will be added in order.
Optional Parameters:
- title: An optional title for the dashboard tile.
- pivots, filters, sorts, limit, query_timezone: These query parameters are
inherited from the `query` tool and can be used to customize the tile's query.
- vis_config: A JSON object defining the visualization settings for this tile.
The structure and options are the same as for the `query_url` tool's `vis_config`.
Connecting to Dashboard Filters:
A dashboard element can be connected to one or more dashboard filters (created with
`add_dashboard_filter`). To do this, specify the `name` of the dashboard filter
and the `field` from the element's query that the filter should apply to.
The format for specifying the field is `view_name.field_name`.
```
## Reference
| **field** | **type** | **required** | **description** |
|-------------|:--------:|:------------:|----------------------------------------------------|
| kind | string | true | Must be "looker-add-dashboard-element" |
| source | string | true | Name of the source the SQL should execute on. |
| description | string | true | Description of the tool that is passed to the LLM. |
|:------------|:--------:|:------------:|----------------------------------------------------|
| kind | string | true | Must be "looker-add-dashboard-element". |
| source | string | true | Name of the source the SQL should execute on. |
| description | string | true | Description of the tool that is passed to the LLM. |

75
docs/en/resources/tools/looker/looker-add-dashboard-filter.md Normal file
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@@ -0,0 +1,75 @@
---
title: "looker-add-dashboard-filter"
type: docs
weight: 1
description: >
The "looker-add-dashboard-filter" tool adds a filter to a specified dashboard.
aliases:
- /resources/tools/looker-add-dashboard-filter
---
## About
The `looker-add-dashboard-filter` tool adds a filter to a specified Looker dashboard.
CRITICAL ORDER OF OPERATIONS:
1. Create a dashboard using `make_dashboard`.
2. Add all desired filters using this tool (`add_dashboard_filter`).
3. Finally, add dashboard elements (tiles) using `add_dashboard_element`.
It's compatible with the following sources:
- [looker](../../sources/looker.md)
## Parameters
| **parameter** | **type** | **required** | **default** | **description** |
|:----------------------|:--------:|:-----------------:|:--------------:|-------------------------------------------------------------------------------------------------------------------------------|
| dashboard_id | string | true | none | The ID of the dashboard to add the filter to, obtained from `make_dashboard`. |
| name | string | true | none | A unique internal identifier for the filter. This name is used later in `add_dashboard_element` to bind tiles to this filter. |
| title | string | true | none | The label displayed to users in the Looker UI. |
| filter_type | string | true | `field_filter` | The filter type of filter. Can be `date_filter`, `number_filter`, `string_filter`, or `field_filter`. |
| default_value | string | false | none | The initial value for the filter. |
| model | string | if `field_filter` | none | The name of the LookML model, obtained from `get_models`. |
| explore | string | if `field_filter` | none | The name of the explore within the model, obtained from `get_explores`. |
| dimension | string | if `field_filter` | none | The name of the field (e.g., `view_name.field_name`) to base the filter on, obtained from `get_dimensions`. |
| allow_multiple_values | boolean | false | true | The Dashboard Filter should allow multiple values |
| required | boolean | false | false | The Dashboard Filter is required to run dashboard |
## Example
```yaml
tools:
add_dashboard_filter:
kind: looker-add-dashboard-filter
source: looker-source
description: |
This tool adds a filter to a Looker dashboard.
CRITICAL ORDER OF OPERATIONS:
1. Create a dashboard using `make_dashboard`.
2. Add all desired filters using this tool (`add_dashboard_filter`).
3. Finally, add dashboard elements (tiles) using `add_dashboard_element`.
Parameters:
- dashboard_id (required): The ID from `make_dashboard`.
- name (required): A unique internal identifier for the filter. You will use this `name` later in `add_dashboard_element` to bind tiles to this filter.
- title (required): The label displayed to users in the UI.
- filter_type (required): One of `date_filter`, `number_filter`, `string_filter`, or `field_filter`.
- default_value (optional): The initial value for the filter.
Field Filters (`flter_type: field_filter`):
If creating a field filter, you must also provide:
- model
- explore
- dimension
The filter will inherit suggestions and type information from this LookML field.
```
## Reference
| **field** | **type** | **required** | **description** |
|-------------|:--------:|:------------:|----------------------------------------------------|
| kind | string | true | Must be "looker-add-dashboard-filter". |
| source | string | true | Name of the source the SQL should execute on. |
| description | string | true | Description of the tool that is passed to the LLM. |

7
docs/en/resources/tools/looker/looker-conversational-analytics.md
View File

@@ -34,9 +34,10 @@ tools:
kind: looker-conversational-analytics
source: looker-source
description: |
Use this tool to perform data analysis, get insights,
or answer complex questions about the contents of specific
Looker explores.
Use this tool to ask questions about your data using the Looker Conversational
Analytics API. You must provide a natural language query and a list of
1 to 5 model and explore combinations (e.g. [{'model': 'the_model', 'explore': 'the_explore'}]).
Use the 'get_models' and 'get_explores' tools to discover available models and explores.
```
## Reference

15
docs/en/resources/tools/looker/looker-create-project-file.md
View File

@@ -27,13 +27,18 @@ tools:
kind: looker-create-project-file
source: looker-source
description: |
create_project_file Tool
This tool creates a new LookML file within a specified project, populating
it with the provided content.
Given a project_id and a file path within the project, as well as the content
of a LookML file, this tool will create a new file within the project.
Prerequisite: The Looker session must be in Development Mode. Use `dev_mode: true` first.
This tool must be called after the dev_mode tool has changed the session to
dev mode.
Parameters:
- project_id (required): The unique ID of the LookML project.
- file_path (required): The desired path and filename for the new file within the project.
- content (required): The full LookML content to write into the new file.
Output:
A confirmation message upon successful file creation.
```
## Reference

14
docs/en/resources/tools/looker/looker-delete-project-file.md
View File

@@ -26,13 +26,17 @@ tools:
kind: looker-delete-project-file
source: looker-source
description: |
delete_project_file Tool
This tool permanently deletes a specified LookML file from within a project.
Use with caution, as this action cannot be undone through the API.
Given a project_id and a file path within the project, this tool will delete
the file from the project.
Prerequisite: The Looker session must be in Development Mode. Use `dev_mode: true` first.
This tool must be called after the dev_mode tool has changed the session to
dev mode.
Parameters:
- project_id (required): The unique ID of the LookML project.
- file_path (required): The exact path to the LookML file to delete within the project.
Output:
A confirmation message upon successful file deletion.
```
## Reference

9
docs/en/resources/tools/looker/looker-dev-mode.md
View File

@@ -27,10 +27,13 @@ tools:
kind: looker-dev-mode
source: looker-source
description: |
dev_mode Tool
This tool allows toggling the Looker IDE session between Development Mode and Production Mode.
Development Mode enables making and testing changes to LookML projects.
Passing true to this tool switches the session to dev mode. Passing false to this tool switches the
session to production mode.
Parameters:
- enable (required): A boolean value.
- `true`: Switches the current session to Development Mode.
- `false`: Switches the current session to Production Mode.
```
## Reference

14
docs/en/resources/tools/looker/looker-generate-embed-url.md
View File

@@ -36,11 +36,17 @@ tools:
kind: looker-generate-embed-url
source: looker-source
description: |
generate_embed_url Tool
This tool generates a signed, private embed URL for specific Looker content,
allowing users to access it directly.
This tool generates an embeddable URL for Looker content.
You need to provide the type of content (e.g., 'dashboards', 'looks', 'query-visualization')
and the ID of the content.
Parameters:
- type (required): The type of content to embed. Common values include:
- `dashboards`
- `looks`
- `explore`
- id (required): The unique identifier for the content.
- For dashboards and looks, use the numeric ID (e.g., "123").
- For explores, use the format "model_name/explore_name".
```
## Reference

12
docs/en/resources/tools/looker/looker-get-connection-databases.md
View File

@@ -26,10 +26,16 @@ tools:
kind: looker-get-connection-databases
source: looker-source
description: |
get_connection_databases Tool
This tool retrieves a list of databases available through a specified Looker connection.
This is only applicable for connections that support multiple databases.
Use `get_connections` to check if a connection supports multiple databases.
This tool will list the databases available from a connection if the connection
supports multiple databases.
Parameters:
- connection_name (required): The name of the database connection, obtained from `get_connections`.
Output:
A JSON array of strings, where each string is the name of an available database.
If the connection does not support multiple databases, an empty list or an error will be returned.
```
## Reference

12
docs/en/resources/tools/looker/looker-get-connection-schemas.md
View File

@@ -26,10 +26,16 @@ tools:
kind: looker-get-connection-schemas
source: looker-source
description: |
get_connection_schemas Tool
This tool retrieves a list of database schemas available through a specified
Looker connection.
This tool will list the schemas available from a connection, filtered by
an optional database name.
Parameters:
- connection_name (required): The name of the database connection, obtained from `get_connections`.
- database (optional): An optional database name to filter the schemas.
Only applicable for connections that support multiple databases.
Output:
A JSON array of strings, where each string is the name of an available schema.
```
## Reference

17
docs/en/resources/tools/looker/looker-get-connection-table-columns.md
View File

@@ -26,11 +26,20 @@ tools:
kind: looker-get-connection-table-columns
source: looker-source
description: |
get_connection_table_columns Tool
This tool retrieves a list of columns for one or more specified tables within a
given database schema and connection.
This tool will list the columns available from a connection, for all the tables
given in a comma separated list of table names, filtered by the
schema name and optional database name.
Parameters:
- connection_name (required): The name of the database connection, obtained from `get_connections`.
- schema (required): The name of the schema where the tables reside, obtained from `get_connection_schemas`.
- tables (required): A comma-separated string of table names for which to retrieve columns
(e.g., "users,orders,products"), obtained from `get_connection_tables`.
- database (optional): The name of the database to filter by. Only applicable for connections
that support multiple databases (check with `get_connections`).
Output:
A JSON array of objects, where each object represents a column and contains details
such as `table_name`, `column_name`, `data_type`, and `is_nullable`.
```
## Reference

13
docs/en/resources/tools/looker/looker-get-connection-tables.md
View File

@@ -27,10 +27,17 @@ tools:
kind: looker-get-connection-tables
source: looker-source
description: |
get_connection_tables Tool
This tool retrieves a list of tables available within a specified database schema
through a Looker connection.
This tool will list the tables available from a connection, filtered by the
schema name and optional database name.
Parameters:
- connection_name (required): The name of the database connection, obtained from `get_connections`.
- schema (required): The name of the schema to list tables from, obtained from `get_connection_schemas`.
- database (optional): The name of the database to filter by. Only applicable for connections
that support multiple databases (check with `get_connections`).
Output:
A JSON array of strings, where each string is the name of an available table.
```
## Reference

15
docs/en/resources/tools/looker/looker-get-connections.md
View File

@@ -26,11 +26,18 @@ tools:
kind: looker-get-connections
source: looker-source
description: |
get_connections Tool
This tool retrieves a list of all database connections configured in the Looker system.
This tool will list all the connections available in the Looker system, as
well as the dialect name, the default schema, the database if applicable,
and whether the connection supports multiple databases.
Parameters:
This tool takes no parameters.
Output:
A JSON array of objects, each representing a database connection and including details such as:
- `name`: The connection's unique identifier.
- `dialect`: The database dialect (e.g., "mysql", "postgresql", "bigquery").
- `default_schema`: The default schema for the connection.
- `database`: The associated database name (if applicable).
- `supports_multiple_databases`: A boolean indicating if the connection can access multiple databases.
```
## Reference

42
docs/en/resources/tools/looker/looker-get-dashboards.md
View File

@@ -29,25 +29,29 @@ default to 100 and 0.
```yaml
tools:
get_dashboards:
kind: looker-get-dashboards
source: looker-source
description: |
get_dashboards Tool
This tool is used to search for saved dashboards in a Looker instance.
String search params use case-insensitive matching. String search
params can contain % and '_' as SQL LIKE pattern match wildcard
expressions. example="dan%" will match "danger" and "Danzig" but
not "David" example="D_m%" will match "Damage" and "dump".
Most search params can accept "IS NULL" and "NOT NULL" as special
expressions to match or exclude (respectively) rows where the
column is null.
The limit and offset are used to paginate the results.
The result of the get_dashboards tool is a list of json objects.
get_dashboards:
kind: looker-get-dashboards
source: looker-source
description: |
This tool searches for saved dashboards in a Looker instance. It returns a list of JSON objects, each representing a dashboard.
Search Parameters:
- title (optional): Filter by dashboard title (supports wildcards).
- folder_id (optional): Filter by the ID of the folder where the dashboard is saved.
- user_id (optional): Filter by the ID of the user who created the dashboard.
- description (optional): Filter by description content (supports wildcards).
- id (optional): Filter by specific dashboard ID.
- limit (optional): Maximum number of results to return. Defaults to a system limit.
- offset (optional): Starting point for pagination.
String Search Behavior:
- Case-insensitive matching.
- Supports SQL LIKE pattern match wildcards:
- `%`: Matches any sequence of zero or more characters. (e.g., `"finan%"` matches "financial", "finance")
- `_`: Matches any single character. (e.g., `"s_les"` matches "sales")
- Special expressions for null checks:
- `"IS NULL"`: Matches dashboards where the field is null.
- `"NOT NULL"`: Excludes dashboards where the field is null.
```
## Reference

20
docs/en/resources/tools/looker/looker-get-dimensions.md
View File

@@ -28,16 +28,20 @@ tools:
kind: looker-get-dimensions
source: looker-source
description: |
The get_dimensions tool retrieves the list of dimensions defined in
an explore.
This tool retrieves a list of dimensions defined within a specific Looker explore.
Dimensions are non-aggregatable attributes or characteristics of your data
(e.g., product name, order date, customer city) that can be used for grouping,
filtering, or segmenting query results.
It takes two parameters, the model_name looked up from get_models and the
explore_name looked up from get_explores.
Parameters:
- model_name (required): The name of the LookML model, obtained from `get_models`.
- explore_name (required): The name of the explore within the model, obtained from `get_explores`.
If this returns a suggestions field for a dimension, the contents of suggestions
can be used as filters for this field. If this returns a suggest_explore and
suggest_dimension, a query against that explore and dimension can be used to find
valid filters for this field.
Output Details:
- If a dimension includes a `suggestions` field, its contents are valid values
that can be used directly as filters for that dimension.
- If a `suggest_explore` and `suggest_dimension` are provided, you can query
that specified explore and dimension to retrieve a list of valid filter values.
```

9
docs/en/resources/tools/looker/looker-get-explores.md
View File

@@ -40,10 +40,13 @@ tools:
kind: looker-get-explores
source: looker-source
description: |
The get_explores tool retrieves the list of explores defined in a LookML model
in the Looker system.
This tool retrieves a list of explores defined within a specific LookML model.
Explores represent a curated view of your data, typically joining several
tables together to allow for focused analysis on a particular subject area.
The output provides details like the explore's `name` and `label`.
It takes one parameter, the model_name looked up from get_models.
Parameters:
- model_name (required): The name of the LookML model, obtained from `get_models`.
```
## Reference

17
docs/en/resources/tools/looker/looker-get-filters.md
View File

@@ -24,15 +24,22 @@ It's compatible with the following sources:
```yaml
tools:
get_dimensions:
get_filters:
kind: looker-get-filters
source: looker-source
description: |
The get_filters tool retrieves the list of filters defined in
an explore.
This tool retrieves a list of "filter-only fields" defined within a specific
Looker explore. These are special fields defined in LookML specifically to
create user-facing filter controls that do not directly affect the `GROUP BY`
clause of the SQL query. They are often used in conjunction with liquid templating
to create dynamic queries.
It takes two parameters, the model_name looked up from get_models and the
explore_name looked up from get_explores.
Note: Regular dimensions and measures can also be used as filters in a query.
This tool *only* returns fields explicitly defined as `filter:` in LookML.
Parameters:
- model_name (required): The name of the LookML model, obtained from `get_models`.
- explore_name (required): The name of the explore within the model, obtained from `get_explores`.
```
The response is a json array with the following elements:

31
docs/en/resources/tools/looker/looker-get-looks.md
View File

@@ -34,21 +34,26 @@ tools:
kind: looker-get-looks
source: looker-source
description: |
get_looks Tool
This tool searches for saved Looks (pre-defined queries and visualizations)
in a Looker instance. It returns a list of JSON objects, each representing a Look.
This tool is used to search for saved looks in a Looker instance.
String search params use case-insensitive matching. String search
params can contain % and '_' as SQL LIKE pattern match wildcard
expressions. example="dan%" will match "danger" and "Danzig" but
not "David" example="D_m%" will match "Damage" and "dump".
Search Parameters:
- title (optional): Filter by Look title (supports wildcards).
- folder_id (optional): Filter by the ID of the folder where the Look is saved.
- user_id (optional): Filter by the ID of the user who created the Look.
- description (optional): Filter by description content (supports wildcards).
- id (optional): Filter by specific Look ID.
- limit (optional): Maximum number of results to return. Defaults to a system limit.
- offset (optional): Starting point for pagination.
Most search params can accept "IS NULL" and "NOT NULL" as special
expressions to match or exclude (respectively) rows where the
column is null.
The limit and offset are used to paginate the results.
The result of the get_looks tool is a list of json objects.
String Search Behavior:
- Case-insensitive matching.
- Supports SQL LIKE pattern match wildcards:
- `%`: Matches any sequence of zero or more characters. (e.g., `"dan%"` matches "danger", "Danzig")
- `_`: Matches any single character. (e.g., `"D_m%"` matches "Damage", "dump")
- Special expressions for null checks:
- `"IS NULL"`: Matches Looks where the field is null.
- `"NOT NULL"`: Excludes Looks where the field is null.
```
## Reference

19
docs/en/resources/tools/looker/looker-get-measures.md
View File

@@ -28,16 +28,19 @@ tools:
kind: looker-get-measures
source: looker-source
description: |
The get_measures tool retrieves the list of measures defined in
an explore.
This tool retrieves a list of measures defined within a specific Looker explore.
Measures are aggregatable metrics (e.g., total sales, average price, count of users)
that are used for calculations and quantitative analysis in your queries.
It takes two parameters, the model_name looked up from get_models and the
explore_name looked up from get_explores.
Parameters:
- model_name (required): The name of the LookML model, obtained from `get_models`.
- explore_name (required): The name of the explore within the model, obtained from `get_explores`.
If this returns a suggestions field for a measure, the contents of suggestions
can be used as filters for this field. If this returns a suggest_explore and
suggest_dimension, a query against that explore and dimension can be used to find
valid filters for this field.
Output Details:
- If a measure includes a `suggestions` field, its contents are valid values
that can be used directly as filters for that measure.
- If a `suggest_explore` and `suggest_dimension` are provided, you can query
that specified explore and dimension to retrieve a list of valid filter values.
```

7
docs/en/resources/tools/looker/looker-get-models.md
View File

@@ -26,9 +26,12 @@ tools:
kind: looker-get-models
source: looker-source
description: |
The get_models tool retrieves the list of LookML models in the Looker system.
This tool retrieves a list of available LookML models in the Looker instance.
LookML models define the data structure and relationships that users can query.
The output includes details like the model's `name` and `label`, which are
essential for subsequent calls to tools like `get_explores` or `query`.
It takes no parameters.
This tool takes no parameters.
```
## Reference

12
docs/en/resources/tools/looker/looker-get-parameters.md
View File

@@ -28,11 +28,15 @@ tools:
kind: looker-get-parameters
source: looker-source
description: |
The get_parameters tool retrieves the list of parameters defined in
an explore.
This tool retrieves a list of parameters defined within a specific Looker explore.
LookML parameters are dynamic input fields that allow users to influence query
behavior without directly modifying the underlying LookML. They are often used
with `liquid` templating to create flexible dashboards and reports, enabling
users to choose dimensions, measures, or other query components at runtime.
It takes two parameters, the model_name looked up from get_models and the
explore_name looked up from get_explores.
Parameters:
- model_name (required): The name of the LookML model, obtained from `get_models`.
- explore_name (required): The name of the explore within the model, obtained from `get_explores`.
```
The response is a json array with the following elements:

11
docs/en/resources/tools/looker/looker-get-project-file.md
View File

@@ -26,10 +26,15 @@ tools:
kind: looker-get-project-file
source: looker-source
description: |
get_project_file Tool
This tool retrieves the raw content of a specific LookML file from within a project.
Given a project_id and a file path within the project, this tool returns
the contents of the LookML file.
Parameters:
- project_id (required): The unique ID of the LookML project, obtained from `get_projects`.
- file_path (required): The path to the LookML file within the project,
typically obtained from `get_project_files`.
Output:
The raw text content of the specified LookML file.
```
## Reference

11
docs/en/resources/tools/looker/looker-get-project-files.md
View File

@@ -26,10 +26,15 @@ tools:
kind: looker-get-project-files
source: looker-source
description: |
get_project_files Tool
This tool retrieves a list of all LookML files within a specified project,
providing details about each file.
Given a project_id this tool returns the details about
the LookML files that make up that project.
Parameters:
- project_id (required): The unique ID of the LookML project, obtained from `get_projects`.
Output:
A JSON array of objects, each representing a LookML file and containing
details such as `path`, `id`, `type`, and `git_status`.
```
## Reference

12
docs/en/resources/tools/looker/looker-get-projects.md
View File

@@ -26,10 +26,16 @@ tools:
kind: looker-get-projects
source: looker-source
description: |
get_projects Tool
This tool retrieves a list of all LookML projects available on the Looker instance.
It is useful for identifying projects before performing actions like retrieving
project files or making modifications.
This tool returns the project_id and project_name for
all the LookML projects on the looker instance.
Parameters:
This tool takes no parameters.
Output:
A JSON array of objects, each containing the `project_id` and `project_name`
for a LookML project.
```
## Reference

19
docs/en/resources/tools/looker/looker-health-analyze.md
View File

@@ -42,17 +42,18 @@ tools:
kind: looker-health-analyze
source: looker-source
description: |
health-analyze Tool
This tool calculates the usage statistics for Looker projects, models, and explores.
This tool calculates the usage of projects, models and explores.
Parameters:
- action (required): The type of resource to analyze. Can be `"projects"`, `"models"`, or `"explores"`.
- project (optional): The specific project ID to analyze.
- model (optional): The specific model name to analyze. Requires `project` if used without `explore`.
- explore (optional): The specific explore name to analyze. Requires `model` if used.
- timeframe (optional): The lookback period in days for usage data. Defaults to `90` days.
- min_queries (optional): The minimum number of queries for a resource to be considered active. Defaults to `1`.
It accepts 6 parameters:
1. `action`: can be "projects", "models", or "explores"
2. `project`: the project to analyze (optional)
3. `model`: the model to analyze (optional)
4. `explore`: the explore to analyze (optional)
5. `timeframe`: the lookback period in days, default is 90
6. `min_queries`: the minimum number of queries to consider a resource as active, default is 1
Output:
The result is a JSON object containing usage metrics for the specified resources.
```
## Reference

28
docs/en/resources/tools/looker/looker-health-pulse.md
View File

@@ -49,20 +49,22 @@ tools:
kind: looker-health-pulse
source: looker-source
description: |
health-pulse Tool
This tool performs various health checks on a Looker instance.
This tool takes the pulse of a Looker instance by taking
one of the following actions:
1. `check_db_connections`,
2. `check_dashboard_performance`,
3. `check_dashboard_errors`,
4. `check_explore_performance`,
5. `check_schedule_failures`, or
6. `check_legacy_features`
The `check_legacy_features` action is only available in Looker Core. If
it is called on a Looker Core instance, you will get a notice. That notice
should not be reported as an error.
Parameters:
- action (required): Specifies the type of health check to perform.
Choose one of the following:
- `check_db_connections`: Verifies database connectivity.
- `check_dashboard_performance`: Assesses dashboard loading performance.
- `check_dashboard_errors`: Identifies errors within dashboards.
- `check_explore_performance`: Evaluates explore query performance.
- `check_schedule_failures`: Reports on failed scheduled deliveries.
- `check_legacy_features`: Checks for the usage of legacy features.
Note on `check_legacy_features`:
This action is exclusively available in Looker Core instances. If invoked
on a non-Looker Core instance, it will return a notice rather than an error.
This notice should be considered normal behavior and not an indication of an issue.
```
## Reference

23
docs/en/resources/tools/looker/looker-health-vacuum.md
View File

@@ -39,20 +39,19 @@ tools:
kind: looker-health-vacuum
source: looker-source
description: |
health-vacuum Tool
This tool identifies and suggests LookML models or explores that can be
safely removed due to inactivity or low usage.
This tool suggests models or explores that can removed
because they are unused.
Parameters:
- action (required): The type of resource to analyze for removal candidates. Can be `"models"` or `"explores"`.
- project (optional): The specific project ID to consider.
- model (optional): The specific model name to consider. Requires `project` if used without `explore`.
- explore (optional): The specific explore name to consider. Requires `model` if used.
- timeframe (optional): The lookback period in days to assess usage. Defaults to `90` days.
- min_queries (optional): The minimum number of queries for a resource to be considered active. Defaults to `1`.
It accepts 6 parameters:
1. `action`: can be "models" or "explores"
2. `project`: the project to vacuum (optional)
3. `model`: the model to vacuum (optional)
4. `explore`: the explore to vacuum (optional)
5. `timeframe`: the lookback period in days, default is 90
6. `min_queries`: the minimum number of queries to consider a resource as active, default is 1
The result is a list of objects that are candidates for deletion.
Output:
A JSON array of objects, each representing a model or explore that is a candidate for deletion due to low usage.
```
| **field** | **type** | **required** | **description** |

21
docs/en/resources/tools/looker/looker-make-dashboard.md
View File

@@ -30,18 +30,19 @@ tools:
kind: looker-make-dashboard
source: looker-source
description: |
make_dashboard Tool
This tool creates a new, empty dashboard in Looker. Dashboards are stored
in the user's personal folder, and the dashboard name must be unique.
After creation, use `add_dashboard_filter` to add filters and
`add_dashboard_element` to add content tiles.
This tool creates a new dashboard in Looker. The dashboard is
initially empty and the add_dashboard_element tool is used to
add content to the dashboard.
Required Parameters:
- title (required): A unique title for the new dashboard.
- description (required): A brief description of the dashboard's purpose.
The newly created dashboard will be created in the user's
personal folder in looker. The dashboard name must be unique.
The result is a json document with a link to the newly
created dashboard and the id of the dashboard. Use the id
when calling add_dashboard_element.
Output:
A JSON object containing a link (`url`) to the newly created dashboard and
its unique `id`. This `dashboard_id` is crucial for subsequent calls to
`add_dashboard_filter` and `add_dashboard_element`.
```
## Reference

26
docs/en/resources/tools/looker/looker-make-look.md
View File

@@ -40,20 +40,24 @@ tools:
kind: looker-make-look
source: looker-source
description: |
make_look Tool
This tool creates a new Look (saved query with visualization) in Looker.
The Look will be saved in the user's personal folder, and its name must be unique.
This tool creates a new look in Looker, using the query
parameters and the vis_config specified.
Required Parameters:
- title: A unique title for the new Look.
- description: A brief description of the Look's purpose.
- model_name: The name of the LookML model (from `get_models`).
- explore_name: The name of the explore (from `get_explores`).
- fields: A list of field names (dimensions, measures, filters, or parameters) to include in the query.
Most of the parameters are the same as the query_url
tool. In addition, there is a title and a description
that must be provided.
Optional Parameters:
- pivots, filters, sorts, limit, query_timezone: These parameters are identical
to those described for the `query` tool.
- vis_config: A JSON object defining the visualization settings for the Look.
The structure and options are the same as for the `query_url` tool's `vis_config`.
The newly created look will be created in the user's
personal folder in looker. The look name must be unique.
The result is a json document with a link to the newly
created look.
Output:
A JSON object containing a link (`url`) to the newly created Look, along with its `id` and `slug`.
```
## Reference

39
docs/en/resources/tools/looker/looker-query-sql.md
View File

@@ -41,38 +41,17 @@ tools:
kind: looker-query-sql
source: looker-source
description: |
Query SQL Tool
This tool generates the underlying SQL query that Looker would execute
against the database for a given set of parameters. It is useful for
understanding how Looker translates a request into SQL.
This tool is used to generate a sql query against the LookML model. The
model, explore, and fields list must be specified. Pivots,
filters and sorts are optional.
Parameters:
All parameters for this tool are identical to those of the `query` tool.
This includes `model_name`, `explore_name`, `fields` (required),
and optional parameters like `pivots`, `filters`, `sorts`, `limit`, and `query_timezone`.
The model can be found from the get_models tool. The explore
can be found from the get_explores tool passing in the model.
The fields can be found from the get_dimensions, get_measures,
get_filters, and get_parameters tools, passing in the model
and the explore.
Provide a model_id and explore_name, then a list
of fields. Optionally a list of pivots can be provided.
The pivots must also be included in the fields list.
Filters are provided as a map of {"field.id": "condition",
"field.id2": "condition2", ...}. Do not put the field.id in
quotes. Filter expressions can be found at
https://cloud.google.com/looker/docs/filter-expressions.
Sorts can be specified like [ "field.id desc 0" ].
An optional row limit can be added. If not provided the limit
will default to 500. "-1" can be specified for unlimited.
An optional query timezone can be added. The query_timezone to
will default to that of the workstation where this MCP server
is running, or Etc/UTC if that can't be determined. Not all
models support custom timezones.
The result of the query tool is the sql string.
Output:
The result of this tool is the raw SQL text.
```
## Reference

22
docs/en/resources/tools/looker/looker-query-url.md
View File

@@ -37,17 +37,21 @@ tools:
kind: looker-query-url
source: looker-source
description: |
Query URL Tool
This tool generates a shareable URL for a Looker query, allowing users to
explore the query further within the Looker UI. It returns the generated URL,
along with the `query_id` and `slug`.
This tool is used to generate the URL of a query in Looker.
The user can then explore the query further inside Looker.
The tool also returns the query_id and slug. The parameters
are the same as the query tool with an additional vis_config
parameter.
Parameters:
All query parameters (e.g., `model_name`, `explore_name`, `fields`, `pivots`,
`filters`, `sorts`, `limit`, `query_timezone`) are the same as the `query` tool.
The vis_config is optional. If provided, it will be used to
control the default visualization for the query. Here are
some notes on making visualizations.
Additionally, it accepts an optional `vis_config` parameter:
- vis_config (optional): A JSON object that controls the default visualization
settings for the generated query.
vis_config Details:
The `vis_config` object supports a wide range of properties for various chart types.
Here are some notes on making visualizations.
### Cartesian Charts (Area, Bar, Column, Line, Scatter)

44
docs/en/resources/tools/looker/looker-query.md
View File

@@ -41,38 +41,24 @@ tools:
kind: looker-query
source: looker-source
description: |
Query Tool
This tool runs a query against a LookML model and returns the results in JSON format.
This tool is used to run a query against the LookML model. The
model, explore, and fields list must be specified. Pivots,
filters and sorts are optional.
Required Parameters:
- model_name: The name of the LookML model (from `get_models`).
- explore_name: The name of the explore (from `get_explores`).
- fields: A list of field names (dimensions, measures, filters, or parameters) to include in the query.
The model can be found from the get_models tool. The explore
can be found from the get_explores tool passing in the model.
The fields can be found from the get_dimensions, get_measures,
get_filters, and get_parameters tools, passing in the model
and the explore.
Optional Parameters:
- pivots: A list of fields to pivot the results by. These fields must also be included in the `fields` list.
- filters: A map of filter expressions, e.g., `{"view.field": "value", "view.date": "7 days"}`.
- Do not quote field names.
- Use `not null` instead of `-NULL`.
- If a value contains a comma, enclose it in single quotes (e.g., "'New York, NY'").
- sorts: A list of fields to sort by, optionally including direction (e.g., `["view.field desc"]`).
- limit: Row limit (default 500). Use "-1" for unlimited.
- query_timezone: specific timezone for the query (e.g. `America/Los_Angeles`).
Provide a model_id and explore_name, then a list
of fields. Optionally a list of pivots can be provided.
The pivots must also be included in the fields list.
Filters are provided as a map of {"field.id": "condition",
"field.id2": "condition2", ...}. Do not put the field.id in
quotes. Filter expressions can be found at
https://cloud.google.com/looker/docs/filter-expressions.
If the condition is a string that contains a comma, use a second
set of quotes. For example, {"user.city": "'New York, NY'"}.
Sorts can be specified like [ "field.id desc 0" ].
An optional row limit can be added. If not provided the limit
will default to 500. "-1" can be specified for unlimited.
An optional query timezone can be added. The query_timezone to
will default to that of the workstation where this MCP server
is running, or Etc/UTC if that can't be determined. Not all
models support custom timezones.
Note: Use `get_dimensions`, `get_measures`, `get_filters`, and `get_parameters` to find valid fields.
The result of the query tool is JSON
```

12
docs/en/resources/tools/looker/looker-run-dashboard.md
View File

@@ -27,11 +27,15 @@ tools:
kind: looker-run-dashboard
source: looker-source
description: |
run_dashboard Tool
This tool executes the queries associated with each tile in a specified dashboard
and returns the aggregated data in a JSON structure.
This tools runs the query associated with each tile in a dashboard
and returns the data in a JSON structure. It accepts the dashboard_id
as the parameter.
Parameters:
- dashboard_id (required): The unique identifier of the dashboard to run,
typically obtained from the `get_dashboards` tool.
Output:
The data from all dashboard tiles is returned as a JSON object.
```
## Reference

12
docs/en/resources/tools/looker/looker-run-look.md
View File

@@ -27,11 +27,15 @@ tools:
kind: looker-run-look
source: looker-source
description: |
run_look Tool
This tool executes the query associated with a saved Look and
returns the resulting data in a JSON structure.
This tool runs the query associated with a look and returns
the data in a JSON structure. It accepts the look_id as the
parameter.
Parameters:
- look_id (required): The unique identifier of the Look to run,
typically obtained from the `get_looks` tool.
Output:
The query results are returned as a JSON object.
```
## Reference

14
docs/en/resources/tools/looker/looker-update-project-file.md
View File

@@ -27,13 +27,17 @@ tools:
kind: looker-update-project-file
source: looker-source
description: |
update_project_file Tool
This tool modifies the content of an existing LookML file within a specified project.
Given a project_id and a file path within the project, as well as the content
of a LookML file, this tool will modify the file within the project.
Prerequisite: The Looker session must be in Development Mode. Use `dev_mode: true` first.
This tool must be called after the dev_mode tool has changed the session to
dev mode.
Parameters:
- project_id (required): The unique ID of the LookML project.
- file_path (required): The exact path to the LookML file to modify within the project.
- content (required): The new, complete LookML content to overwrite the existing file.
Output:
A confirmation message upon successful file modification.
```
## Reference

27
internal/prebuiltconfigs/tools/looker-conversational-analytics.yaml
View File

@@ -29,26 +29,37 @@ tools:
kind: looker-conversational-analytics
source: looker-source
description: |
Use this tool to perform data analysis, get insights,
or answer complex questions about the contents of specific
Looker explores.
Use this tool to ask questions about your data using the Looker Conversational
Analytics API. You must provide a natural language query and a list of
1 to 5 model and explore combinations (e.g. [{'model': 'the_model', 'explore': 'the_explore'}]).
Use the 'get_models' and 'get_explores' tools to discover available models and explores.
get_models:
kind: looker-get-models
source: looker-source
description: |
The get_models tool retrieves the list of LookML models in the Looker system.
get_models Tool
It takes no parameters.
This tool retrieves a list of available LookML models in the Looker instance.
LookML models define the data structure and relationships that users can query.
The output includes details like the model's `name` and `label`, which are
essential for subsequent calls to tools like `get_explores` or `query`.
This tool takes no parameters.
get_explores:
kind: looker-get-explores
source: looker-source
description: |
The get_explores tool retrieves the list of explores defined in a LookML model
in the Looker system.
get_explores Tool
It takes one parameter, the model_name looked up from get_models.
This tool retrieves a list of explores defined within a specific LookML model.
Explores represent a curated view of your data, typically joining several
tables together to allow for focused analysis on a particular subject area.
The output provides details like the explore's `name` and `label`.
Parameters:
- model_name (required): The name of the LookML model, obtained from `get_models`.
toolsets:
looker_conversational_analytics_tools:

595
internal/prebuiltconfigs/tools/looker.yaml
View File

@@ -30,136 +30,151 @@ tools:
kind: looker-get-models
source: looker-source
description: |
The get_models tool retrieves the list of LookML models in the Looker system.
This tool retrieves a list of available LookML models in the Looker instance.
LookML models define the data structure and relationships that users can query.
The output includes details like the model's `name` and `label`, which are
essential for subsequent calls to tools like `get_explores` or `query`.
It takes no parameters.
This tool takes no parameters.
get_explores:
kind: looker-get-explores
source: looker-source
description: |
The get_explores tool retrieves the list of explores defined in a LookML model
in the Looker system.
This tool retrieves a list of explores defined within a specific LookML model.
Explores represent a curated view of your data, typically joining several
tables together to allow for focused analysis on a particular subject area.
The output provides details like the explore's `name` and `label`.
It takes one parameter, the model_name looked up from get_models.
Parameters:
- model_name (required): The name of the LookML model, obtained from `get_models`.
get_dimensions:
kind: looker-get-dimensions
source: looker-source
description: |
The get_dimensions tool retrieves the list of dimensions defined in
an explore.
This tool retrieves a list of dimensions defined within a specific Looker explore.
Dimensions are non-aggregatable attributes or characteristics of your data
(e.g., product name, order date, customer city) that can be used for grouping,
filtering, or segmenting query results.
It takes two parameters, the model_name looked up from get_models and the
explore_name looked up from get_explores.
Parameters:
- model_name (required): The name of the LookML model, obtained from `get_models`.
- explore_name (required): The name of the explore within the model, obtained from `get_explores`.
If this returns a suggestions field for a dimension, the contents of suggestions
can be used as filters for this field. If this returns a suggest_explore and
suggest_dimension, a query against that explore and dimension can be used to find
valid filters for this field.
Output Details:
- If a dimension includes a `suggestions` field, its contents are valid values
that can be used directly as filters for that dimension.
- If a `suggest_explore` and `suggest_dimension` are provided, you can query
that specified explore and dimension to retrieve a list of valid filter values.
get_measures:
kind: looker-get-measures
source: looker-source
description: |
The get_measures tool retrieves the list of measures defined in
an explore.
This tool retrieves a list of measures defined within a specific Looker explore.
Measures are aggregatable metrics (e.g., total sales, average price, count of users)
that are used for calculations and quantitative analysis in your queries.
It takes two parameters, the model_name looked up from get_models and the
explore_name looked up from get_explores.
Parameters:
- model_name (required): The name of the LookML model, obtained from `get_models`.
- explore_name (required): The name of the explore within the model, obtained from `get_explores`.
If this returns a suggestions field for a measure, the contents of suggestions
can be used as filters for this field. If this returns a suggest_explore and
suggest_dimension, a query against that explore and dimension can be used to find
valid filters for this field.
Output Details:
- If a measure includes a `suggestions` field, its contents are valid values
that can be used directly as filters for that measure.
- If a `suggest_explore` and `suggest_dimension` are provided, you can query
that specified explore and dimension to retrieve a list of valid filter values.
get_filters:
kind: looker-get-filters
source: looker-source
description: |
The get_filters tool retrieves the list of filters defined in
an explore.
This tool retrieves a list of "filter-only fields" defined within a specific
Looker explore. These are special fields defined in LookML specifically to
create user-facing filter controls that do not directly affect the `GROUP BY`
clause of the SQL query. They are often used in conjunction with liquid templating
to create dynamic queries.
It takes two parameters, the model_name looked up from get_models and the
explore_name looked up from get_explores.
Note: Regular dimensions and measures can also be used as filters in a query.
This tool *only* returns fields explicitly defined as `filter:` in LookML.
Parameters:
- model_name (required): The name of the LookML model, obtained from `get_models`.
- explore_name (required): The name of the explore within the model, obtained from `get_explores`.
get_parameters:
kind: looker-get-parameters
source: looker-source
description: |
The get_parameters tool retrieves the list of parameters defined in
an explore.
This tool retrieves a list of parameters defined within a specific Looker explore.
LookML parameters are dynamic input fields that allow users to influence query
behavior without directly modifying the underlying LookML. They are often used
with `liquid` templating to create flexible dashboards and reports, enabling
users to choose dimensions, measures, or other query components at runtime.
It takes two parameters, the model_name looked up from get_models and the
explore_name looked up from get_explores.
Parameters:
- model_name (required): The name of the LookML model, obtained from `get_models`.
- explore_name (required): The name of the explore within the model, obtained from `get_explores`.
query:
kind: looker-query
source: looker-source
description: |
Query Tool
This tool runs a query against a LookML model and returns the results in JSON format.
This tool is used to run a query against the LookML model. The
model, explore, and fields list must be specified. Pivots,
filters and sorts are optional.
Required Parameters:
- model_name: The name of the LookML model (from `get_models`).
- explore_name: The name of the explore (from `get_explores`).
- fields: A list of field names (dimensions, measures, filters, or parameters) to include in the query.
The model can be found from the get_models tool. The explore
can be found from the get_explores tool passing in the model.
The fields can be found from the get_dimensions, get_measures,
get_filters, and get_parameters tools, passing in the model
and the explore.
Optional Parameters:
- pivots: A list of fields to pivot the results by. These fields must also be included in the `fields` list.
- filters: A map of filter expressions, e.g., `{"view.field": "value", "view.date": "7 days"}`.
- Do not quote field names.
- Use `not null` instead of `-NULL`.
- If a value contains a comma, enclose it in single quotes (e.g., "'New York, NY'").
- sorts: A list of fields to sort by, optionally including direction (e.g., `["view.field desc"]`).
- limit: Row limit (default 500). Use "-1" for unlimited.
- query_timezone: specific timezone for the query (e.g. `America/Los_Angeles`).
Provide a model_id and explore_name, then a list
of fields. Optionally a list of pivots can be provided.
The pivots must also be included in the fields list.
Filters are provided as a map of {"field.id": "condition",
"field.id2": "condition2", ...}. Do not put the field.id in
quotes. Filter expressions can be found at
https://cloud.google.com/looker/docs/filter-expressions. There
is one mistake in that, however, Use `not null` instead of `-NULL`.
If the condition is a string that contains a comma, use a second
set of quotes. For example, {"user.city": "'New York, NY'"}.
Sorts can be specified like [ "field.id desc 0" ].
An optional row limit can be added. If not provided the limit
will default to 500. "-1" can be specified for unlimited.
An optional query timezone can be added. The query_timezone to
will default to that of the workstation where this MCP server
is running, or Etc/UTC if that can't be determined. Not all
models support custom timezones.
The result of the query tool is JSON
Note: Use `get_dimensions`, `get_measures`, `get_filters`, and `get_parameters` to find valid fields.
query_sql:
kind: looker-query-sql
source: looker-source
description: |
Query SQL Tool
This tool generates the underlying SQL query that Looker would execute
against the database for a given set of parameters. It is useful for
understanding how Looker translates a request into SQL.
This tool is used to generate the SQL that Looker would
run against the underlying database. The parameters are
the same as the query tool.
Parameters:
All parameters for this tool are identical to those of the `query` tool.
This includes `model_name`, `explore_name`, `fields` (required),
and optional parameters like `pivots`, `filters`, `sorts`, `limit`, and `query_timezone`.
The result of the query sql tool is SQL text.
Output:
The result of this tool is the raw SQL text.
query_url:
kind: looker-query-url
source: looker-source
description: |
Query URL Tool
This tool generates a shareable URL for a Looker query, allowing users to
explore the query further within the Looker UI. It returns the generated URL,
along with the `query_id` and `slug`.
This tool is used to generate the URL of a query in Looker.
The user can then explore the query further inside Looker.
The tool also returns the query_id and slug. The parameters
are the same as the query tool with an additional vis_config
parameter.
Parameters:
All query parameters (e.g., `model_name`, `explore_name`, `fields`, `pivots`,
`filters`, `sorts`, `limit`, `query_timezone`) are the same as the `query` tool.
The vis_config is optional. If provided, it will be used to
control the default visualization for the query. Here are
some notes on making visualizations.
Additionally, it accepts an optional `vis_config` parameter:
- vis_config (optional): A JSON object that controls the default visualization
settings for the generated query.
vis_config Details:
The `vis_config` object supports a wide range of properties for various chart types.
Here are some notes on making visualizations.
### Cartesian Charts (Area, Bar, Column, Line, Scatter)
@@ -599,286 +614,432 @@ tools:
kind: looker-get-looks
source: looker-source
description: |
get_looks Tool
This tool searches for saved Looks (pre-defined queries and visualizations)
in a Looker instance. It returns a list of JSON objects, each representing a Look.
This tool is used to search for saved looks in a Looker instance.
String search params use case-insensitive matching. String search
params can contain % and '_' as SQL LIKE pattern match wildcard
expressions. example="dan%" will match "danger" and "Danzig" but
not "David" example="D_m%" will match "Damage" and "dump".
Search Parameters:
- title (optional): Filter by Look title (supports wildcards).
- folder_id (optional): Filter by the ID of the folder where the Look is saved.
- user_id (optional): Filter by the ID of the user who created the Look.
- description (optional): Filter by description content (supports wildcards).
- id (optional): Filter by specific Look ID.
- limit (optional): Maximum number of results to return. Defaults to a system limit.
- offset (optional): Starting point for pagination.
Most search params can accept "IS NULL" and "NOT NULL" as special
expressions to match or exclude (respectively) rows where the
column is null.
The limit and offset are used to paginate the results.
The result of the get_looks tool is a list of json objects.
String Search Behavior:
- Case-insensitive matching.
- Supports SQL LIKE pattern match wildcards:
- `%`: Matches any sequence of zero or more characters. (e.g., `"dan%"` matches "danger", "Danzig")
- `_`: Matches any single character. (e.g., `"D_m%"` matches "Damage", "dump")
- Special expressions for null checks:
- `"IS NULL"`: Matches Looks where the field is null.
- `"NOT NULL"`: Excludes Looks where the field is null.
run_look:
kind: looker-run-look
source: looker-source
description: |
run_look Tool
This tool executes the query associated with a saved Look and
returns the resulting data in a JSON structure.
This tool runs the query associated with a look and returns
the data in a JSON structure. It accepts the look_id as the
parameter.
Parameters:
- look_id (required): The unique identifier of the Look to run,
typically obtained from the `get_looks` tool.
Output:
The query results are returned as a JSON object.
make_look:
kind: looker-make-look
source: looker-source
description: |
make_look Tool
This tool creates a new Look (saved query with visualization) in Looker.
The Look will be saved in the user's personal folder, and its name must be unique.
This tool creates a new look in Looker, using the query
parameters and the vis_config specified.
Required Parameters:
- title: A unique title for the new Look.
- description: A brief description of the Look's purpose.
- model_name: The name of the LookML model (from `get_models`).
- explore_name: The name of the explore (from `get_explores`).
- fields: A list of field names (dimensions, measures, filters, or parameters) to include in the query.
Most of the parameters are the same as the query_url
tool. In addition, there is a title and a description
that must be provided.
Optional Parameters:
- pivots, filters, sorts, limit, query_timezone: These parameters are identical
to those described for the `query` tool.
- vis_config: A JSON object defining the visualization settings for the Look.
The structure and options are the same as for the `query_url` tool's `vis_config`.
The newly created look will be created in the user's
personal folder in looker. The look name must be unique.
The result is a json document with a link to the newly
created look.
Output:
A JSON object containing a link (`url`) to the newly created Look, along with its `id` and `slug`.
get_dashboards:
kind: looker-get-dashboards
source: looker-source
description: |
get_dashboards Tool
This tool searches for saved dashboards in a Looker instance. It returns a list of JSON objects, each representing a dashboard.
This tool is used to search for saved dashboards in a Looker instance.
String search params use case-insensitive matching. String search
params can contain % and '_' as SQL LIKE pattern match wildcard
expressions. example="dan%" will match "danger" and "Danzig" but
not "David" example="D_m%" will match "Damage" and "dump".
Most search params can accept "IS NULL" and "NOT NULL" as special
expressions to match or exclude (respectively) rows where the
column is null.
Search Parameters:
- title (optional): Filter by dashboard title (supports wildcards).
- folder_id (optional): Filter by the ID of the folder where the dashboard is saved.
- user_id (optional): Filter by the ID of the user who created the dashboard.
- description (optional): Filter by description content (supports wildcards).
- id (optional): Filter by specific dashboard ID.
- limit (optional): Maximum number of results to return. Defaults to a system limit.
- offset (optional): Starting point for pagination.
The limit and offset are used to paginate the results.
The result of the get_dashboards tool is a list of json objects.
String Search Behavior:
- Case-insensitive matching.
- Supports SQL LIKE pattern match wildcards:
- `%`: Matches any sequence of zero or more characters. (e.g., `"finan%"` matches "financial", "finance")
- `_`: Matches any single character. (e.g., `"s_les"` matches "sales")
- Special expressions for null checks:
- `"IS NULL"`: Matches dashboards where the field is null.
- `"NOT NULL"`: Excludes dashboards where the field is null.
run_dashboard:
kind: looker-run-dashboard
source: looker-source
description: |
run_dashboard Tool
This tool executes the queries associated with each tile in a specified dashboard
and returns the aggregated data in a JSON structure.
This tools runs the query associated with each tile in a dashboard
and returns the data in a JSON structure. It accepts the dashboard_id
as the parameter.
Parameters:
- dashboard_id (required): The unique identifier of the dashboard to run,
typically obtained from the `get_dashboards` tool.
Output:
The data from all dashboard tiles is returned as a JSON object.
make_dashboard:
kind: looker-make-dashboard
source: looker-source
description: |
make_dashboard Tool
This tool creates a new, empty dashboard in Looker. Dashboards are stored
in the user's personal folder, and the dashboard name must be unique.
After creation, use `add_dashboard_filter` to add filters and
`add_dashboard_element` to add content tiles.
This tool creates a new dashboard in Looker. The dashboard is
initially empty and the add_dashboard_element tool is used to
add content to the dashboard.
Required Parameters:
- title (required): A unique title for the new dashboard.
- description (required): A brief description of the dashboard's purpose.
The newly created dashboard will be created in the user's
personal folder in looker. The dashboard name must be unique.
The result is a json document with a link to the newly
created dashboard and the id of the dashboard. Use the id
when calling add_dashboard_element.
Output:
A JSON object containing a link (`url`) to the newly created dashboard and
its unique `id`. This `dashboard_id` is crucial for subsequent calls to
`add_dashboard_filter` and `add_dashboard_element`.
add_dashboard_element:
kind: looker-add-dashboard-element
source: looker-source
description: |
add_dashboard_element Tool
This tool creates a new tile (element) within an existing Looker dashboard.
Tiles are added in the order this tool is called for a given `dashboard_id`.
This tool creates a new tile in a Looker dashboard using
the query parameters and the vis_config specified.
CRITICAL ORDER OF OPERATIONS:
1. Create the dashboard using `make_dashboard`.
2. Add any dashboard-level filters using `add_dashboard_filter`.
3. Then, add elements (tiles) using this tool.
Most of the parameters are the same as the query_url
tool. In addition, there is a title that may be provided.
The dashboard_id must be specified. That is obtained
from calling make_dashboard.
Required Parameters:
- dashboard_id: The ID of the target dashboard, obtained from `make_dashboard`.
- model_name, explore_name, fields: These query parameters are inherited
from the `query` tool and are required to define the data for the tile.
This tool can be called many times for one dashboard_id
and the resulting tiles will be added in order.
Optional Parameters:
- title: An optional title for the dashboard tile.
- pivots, filters, sorts, limit, query_timezone: These query parameters are
inherited from the `query` tool and can be used to customize the tile's query.
- vis_config: A JSON object defining the visualization settings for this tile.
The structure and options are the same as for the `query_url` tool's `vis_config`.
Connecting to Dashboard Filters:
A dashboard element can be connected to one or more dashboard filters (created with
`add_dashboard_filter`). To do this, specify the `name` of the dashboard filter
and the `field` from the element's query that the filter should apply to.
The format for specifying the field is `view_name.field_name`.
add_dashboard_filter:
kind: looker-add-dashboard-filter
source: looker-source
description: |
This tool adds a filter to a Looker dashboard.
CRITICAL ORDER OF OPERATIONS:
1. Create a dashboard using `make_dashboard`.
2. Add all desired filters using this tool (`add_dashboard_filter`).
3. Finally, add dashboard elements (tiles) using `add_dashboard_element`.
Parameters:
- dashboard_id (required): The ID from `make_dashboard`.
- name (required): A unique internal identifier for the filter. You will use this `name` later in `add_dashboard_element` to bind tiles to this filter.
- title (required): The label displayed to users in the UI.
- flter_type (required): One of `date_filter`, `number_filter`, `string_filter`, or `field_filter`.
- default_value (optional): The initial value for the filter.
Field Filters (`flter_type: field_filter`):
If creating a field filter, you must also provide:
- model
- explore
- dimension
The filter will inherit suggestions and type information from this LookML field.
generate_embed_url:
kind: looker-generate-embed-url
source: looker-source
description: |
This tool generates a signed, private embed URL for specific Looker content,
allowing users to access it directly.
Parameters:
- type (required): The type of content to embed. Common values include:
- `dashboards`
- `looks`
- `explore`
- id (required): The unique identifier for the content.
- For dashboards and looks, use the numeric ID (e.g., "123").
- For explores, use the format "model_name/explore_name".
health_pulse:
kind: looker-health-pulse
source: looker-source
description: |
health-pulse Tool
This tool performs various health checks on a Looker instance.
This tool takes the pulse of a Looker instance by taking
one of the following actions:
1. `check_db_connections`,
2. `check_dashboard_performance`,
3. `check_dashboard_errors`,
4. `check_explore_performance`,
5. `check_schedule_failures`, or
6. `check_legacy_features`
The `check_legacy_features` action is only available in Looker Core. If
it is called on a Looker Core instance, you will get a notice. That notice
should not be reported as an error.
Parameters:
- action (required): Specifies the type of health check to perform.
Choose one of the following:
- `check_db_connections`: Verifies database connectivity.
- `check_dashboard_performance`: Assesses dashboard loading performance.
- `check_dashboard_errors`: Identifies errors within dashboards.
- `check_explore_performance`: Evaluates explore query performance.
- `check_schedule_failures`: Reports on failed scheduled deliveries.
- `check_legacy_features`: Checks for the usage of legacy features.
Note on `check_legacy_features`:
This action is exclusively available in Looker Core instances. If invoked
on a non-Looker Core instance, it will return a notice rather than an error.
This notice should be considered normal behavior and not an indication of an issue.
health_analyze:
kind: looker-health-analyze
source: looker-source
description: |
health-analyze Tool
This tool calculates the usage statistics for Looker projects, models, and explores.
This tool calculates the usage of projects, models and explores.
Parameters:
- action (required): The type of resource to analyze. Can be `"projects"`, `"models"`, or `"explores"`.
- project (optional): The specific project ID to analyze.
- model (optional): The specific model name to analyze. Requires `project` if used without `explore`.
- explore (optional): The specific explore name to analyze. Requires `model` if used.
- timeframe (optional): The lookback period in days for usage data. Defaults to `90` days.
- min_queries (optional): The minimum number of queries for a resource to be considered active. Defaults to `1`.
It accepts 6 parameters:
1. `action`: can be "projects", "models", or "explores"
2. `project`: the project to analyze (optional)
3. `model`: the model to analyze (optional)
4. `explore`: the explore to analyze (optional)
5. `timeframe`: the lookback period in days, default is 90
6. `min_queries`: the minimum number of queries to consider a resource as active, default is 1
Output:
The result is a JSON object containing usage metrics for the specified resources.
health_vacuum:
kind: looker-health-vacuum
source: looker-source
description: |
health-vacuum Tool
This tool identifies and suggests LookML models or explores that can be
safely removed due to inactivity or low usage.
This tool suggests models or explores that can removed
because they are unused.
Parameters:
- action (required): The type of resource to analyze for removal candidates. Can be `"models"` or `"explores"`.
- project (optional): The specific project ID to consider.
- model (optional): The specific model name to consider. Requires `project` if used without `explore`.
- explore (optional): The specific explore name to consider. Requires `model` if used.
- timeframe (optional): The lookback period in days to assess usage. Defaults to `90` days.
- min_queries (optional): The minimum number of queries for a resource to be considered active. Defaults to `1`.
It accepts 6 parameters:
1. `action`: can be "models" or "explores"
2. `project`: the project to vacuum (optional)
3. `model`: the model to vacuum (optional)
4. `explore`: the explore to vacuum (optional)
5. `timeframe`: the lookback period in days, default is 90
6. `min_queries`: the minimum number of queries to consider a resource as active, default is 1
The result is a list of objects that are candidates for deletion.
Output:
A JSON array of objects, each representing a model or explore that is a candidate for deletion due to low usage.
dev_mode:
kind: looker-dev-mode
source: looker-source
description: |
dev_mode Tool
This tool allows toggling the Looker IDE session between Development Mode and Production Mode.
Development Mode enables making and testing changes to LookML projects.
Passing true to this tool switches the session to dev mode. Passing false to this tool switches the
session to production mode.
Parameters:
- enable (required): A boolean value.
- `true`: Switches the current session to Development Mode.
- `false`: Switches the current session to Production Mode.
get_projects:
kind: looker-get-projects
source: looker-source
description: |
get_projects Tool
This tool retrieves a list of all LookML projects available on the Looker instance.
It is useful for identifying projects before performing actions like retrieving
project files or making modifications.
This tool returns the project_id and project_name for
all the LookML projects on the looker instance.
Parameters:
This tool takes no parameters.
Output:
A JSON array of objects, each containing the `project_id` and `project_name`
for a LookML project.
get_project_files:
kind: looker-get-project-files
source: looker-source
description: |
get_project_files Tool
This tool retrieves a list of all LookML files within a specified project,
providing details about each file.
Given a project_id this tool returns the details about
the LookML files that make up that project.
Parameters:
- project_id (required): The unique ID of the LookML project, obtained from `get_projects`.
Output:
A JSON array of objects, each representing a LookML file and containing
details such as `path`, `id`, `type`, and `git_status`.
get_project_file:
kind: looker-get-project-file
source: looker-source
description: |
get_project_file Tool
This tool retrieves the raw content of a specific LookML file from within a project.
Given a project_id and a file path within the project, this tool returns
the contents of the LookML file.
Parameters:
- project_id (required): The unique ID of the LookML project, obtained from `get_projects`.
- file_path (required): The path to the LookML file within the project,
typically obtained from `get_project_files`.
Output:
The raw text content of the specified LookML file.
create_project_file:
kind: looker-create-project-file
source: looker-source
description: |
create_project_file Tool
This tool creates a new LookML file within a specified project, populating
it with the provided content.
Given a project_id and a file path within the project, as well as the content
of a LookML file, this tool will create a new file within the project.
Prerequisite: The Looker session must be in Development Mode. Use `dev_mode: true` first.
This tool must be called after the dev_mode tool has changed the session to
dev mode.
Parameters:
- project_id (required): The unique ID of the LookML project.
- file_path (required): The desired path and filename for the new file within the project.
- content (required): The full LookML content to write into the new file.
Output:
A confirmation message upon successful file creation.
update_project_file:
kind: looker-update-project-file
source: looker-source
description: |
update_project_file Tool
This tool modifies the content of an existing LookML file within a specified project.
Given a project_id and a file path within the project, as well as the content
of a LookML file, this tool will modify the file within the project.
Prerequisite: The Looker session must be in Development Mode. Use `dev_mode: true` first.
This tool must be called after the dev_mode tool has changed the session to
dev mode.
Parameters:
- project_id (required): The unique ID of the LookML project.
- file_path (required): The exact path to the LookML file to modify within the project.
- content (required): The new, complete LookML content to overwrite the existing file.
Output:
A confirmation message upon successful file modification.
delete_project_file:
kind: looker-delete-project-file
source: looker-source
description: |
delete_project_file Tool
This tool permanently deletes a specified LookML file from within a project.
Use with caution, as this action cannot be undone through the API.
Given a project_id and a file path within the project, this tool will delete
the file from the project.
Prerequisite: The Looker session must be in Development Mode. Use `dev_mode: true` first.
This tool must be called after the dev_mode tool has changed the session to
dev mode.
Parameters:
- project_id (required): The unique ID of the LookML project.
- file_path (required): The exact path to the LookML file to delete within the project.
Output:
A confirmation message upon successful file deletion.
get_connections:
kind: looker-get-connections
source: looker-source
description: |
get_connections Tool
This tool retrieves a list of all database connections configured in the Looker system.
This tool will list all the connections available in the Looker system, as
well as the dialect name, the default schema, the database if applicable,
and whether the connection supports multiple databases.
Parameters:
This tool takes no parameters.
Output:
A JSON array of objects, each representing a database connection and including details such as:
- `name`: The connection's unique identifier.
- `dialect`: The database dialect (e.g., "mysql", "postgresql", "bigquery").
- `default_schema`: The default schema for the connection.
- `database`: The associated database name (if applicable).
- `supports_multiple_databases`: A boolean indicating if the connection can access multiple databases.
get_connection_schemas:
kind: looker-get-connection-schemas
source: looker-source
description: |
get_connection_schemas Tool
This tool retrieves a list of database schemas available through a specified
Looker connection.
This tool will list the schemas available from a connection, filtered by
an optional database name.
Parameters:
- connection_name (required): The name of the database connection, obtained from `get_connections`.
- database (optional): An optional database name to filter the schemas.
Only applicable for connections that support multiple databases.
Output:
A JSON array of strings, where each string is the name of an available schema.
get_connection_databases:
kind: looker-get-connection-databases
source: looker-source
description: |
get_connection_databases Tool
This tool retrieves a list of databases available through a specified Looker connection.
This is only applicable for connections that support multiple databases.
Use `get_connections` to check if a connection supports multiple databases.
This tool will list the databases available from a connection if the connection
supports multiple databases.
Parameters:
- connection_name (required): The name of the database connection, obtained from `get_connections`.
Output:
A JSON array of strings, where each string is the name of an available database.
If the connection does not support multiple databases, an empty list or an error will be returned.
get_connection_tables:
kind: looker-get-connection-tables
source: looker-source
description: |
get_connection_tables Tool
This tool retrieves a list of tables available within a specified database schema
through a Looker connection.
This tool will list the tables available from a connection, filtered by the
schema name and optional database name.
Parameters:
- connection_name (required): The name of the database connection, obtained from `get_connections`.
- schema (required): The name of the schema to list tables from, obtained from `get_connection_schemas`.
- database (optional): The name of the database to filter by. Only applicable for connections
that support multiple databases (check with `get_connections`).
Output:
A JSON array of strings, where each string is the name of an available table.
get_connection_table_columns:
kind: looker-get-connection-table-columns
source: looker-source
description: |
get_connection_table_columns Tool
This tool retrieves a list of columns for one or more specified tables within a
given database schema and connection.
This tool will list the columns available from a connection, for all the tables
given in a comma separated list of table names, filtered by the
schema name and optional database name.
Parameters:
- connection_name (required): The name of the database connection, obtained from `get_connections`.
- schema (required): The name of the schema where the tables reside, obtained from `get_connection_schemas`.
- tables (required): A comma-separated string of table names for which to retrieve columns
(e.g., "users,orders,products"), obtained from `get_connection_tables`.
- database (optional): The name of the database to filter by. Only applicable for connections
that support multiple databases (check with `get_connections`).
Output:
A JSON array of objects, where each object represents a column and contains details
such as `table_name`, `column_name`, `data_type`, and `is_nullable`.
toolsets:
@@ -899,6 +1060,8 @@ toolsets:
- run_dashboard
- make_dashboard
- add_dashboard_element
- add_dashboard_filter
- generate_embed_url
- health_pulse
- health_analyze
- health_vacuum

59
internal/tools/looker/lookeradddashboardelement/lookeradddashboardelement.go
View File

@@ -86,6 +86,16 @@ func (cfg Config) Initialize(srcs map[string]sources.Source) (tools.Tool, error)
"",
)
params = append(params, vizParameter)
dashFilters := parameters.NewArrayParameterWithRequired("dashboard_filters",
`An array of dashboard filters like [{"dashboard_filter_name": "name", "field": "view_name.field_name"}, ...]`,
false,
parameters.NewMapParameterWithDefault("dashboard_filter",
map[string]any{},
`A dashboard filter like {"dashboard_filter_name": "name", "field": "view_name.field_name"}`,
"",
),
)
params = append(params, dashFilters)
annotations := cfg.Annotations
if annotations == nil {
@@ -142,7 +152,9 @@ func (t Tool) Invoke(ctx context.Context, resourceMgr tools.SourceProvider, para
if err != nil {
return nil, fmt.Errorf("unable to get logger from ctx: %s", err)
}
logger.DebugContext(ctx, "params = ", params)
wq, err := lookercommon.ProcessQueryArgs(ctx, params)
if err != nil {
return nil, fmt.Errorf("error building query request: %w", err)
@@ -155,23 +167,64 @@ func (t Tool) Invoke(ctx context.Context, resourceMgr tools.SourceProvider, para
visConfig := paramsMap["vis_config"].(map[string]any)
wq.VisConfig = &visConfig
qrespFields := "id"
sdk, err := lookercommon.GetLookerSDK(t.UseClientOAuth, t.ApiSettings, t.Client, accessToken)
if err != nil {
return nil, fmt.Errorf("error getting sdk: %w", err)
}
qresp, err := sdk.CreateQuery(*wq, qrespFields, t.ApiSettings)
qresp, err := sdk.CreateQuery(*wq, "id", t.ApiSettings)
if err != nil {
return nil, fmt.Errorf("error making create query request: %w", err)
}
dashFilters := []any{}
if v, ok := paramsMap["dashboard_filters"]; ok {
if v != nil {
dashFilters = paramsMap["dashboard_filters"].([]any)
}
}
var filterables []v4.ResultMakerFilterables
for _, m := range dashFilters {
f := m.(map[string]any)
name, ok := f["dashboard_filter_name"].(string)
if !ok {
return nil, fmt.Errorf("error processing dashboard filter: %w", err)
}
field, ok := f["field"].(string)
if !ok {
return nil, fmt.Errorf("error processing dashboard filter: %w", err)
}
listener := v4.ResultMakerFilterablesListen{
DashboardFilterName: &name,
Field: &field,
}
listeners := []v4.ResultMakerFilterablesListen{listener}
filter := v4.ResultMakerFilterables{
Listen: &listeners,
}
filterables = append(filterables, filter)
}
if len(filterables) == 0 {
filterables = nil
}
wrm := v4.WriteResultMakerWithIdVisConfigAndDynamicFields{
Query: wq,
VisConfig: &visConfig,
Filterables: &filterables,
}
wde := v4.WriteDashboardElement{
DashboardId: &dashboard_id,
Title: &title,
ResultMaker: &wrm,
Query: wq,
QueryId: qresp.Id,
}
switch len(visConfig) {
case 0:
wde.Type = &dataType

248
internal/tools/looker/lookeradddashboardfilter/lookeradddashboardfilter.go Normal file
View File

@@ -0,0 +1,248 @@
// Copyright 2025 Google LLC
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
package lookeradddashboardfilter
import (
"context"
"fmt"
yaml "github.com/goccy/go-yaml"
"github.com/googleapis/genai-toolbox/internal/sources"
lookersrc "github.com/googleapis/genai-toolbox/internal/sources/looker"
"github.com/googleapis/genai-toolbox/internal/tools"
"github.com/googleapis/genai-toolbox/internal/tools/looker/lookercommon"
"github.com/googleapis/genai-toolbox/internal/util"
"github.com/googleapis/genai-toolbox/internal/util/parameters"
"github.com/looker-open-source/sdk-codegen/go/rtl"
v4 "github.com/looker-open-source/sdk-codegen/go/sdk/v4"
)
const kind string = "looker-add-dashboard-filter"
func init() {
if !tools.Register(kind, newConfig) {
panic(fmt.Sprintf("tool kind %q already registered", kind))
}
}
func newConfig(ctx context.Context, name string, decoder *yaml.Decoder) (tools.ToolConfig, error) {
actual := Config{Name: name}
if err := decoder.DecodeContext(ctx, &actual); err != nil {
return nil, err
}
return actual, nil
}
type Config struct {
Name string `yaml:"name" validate:"required"`
Kind string `yaml:"kind" validate:"required"`
Source string `yaml:"source" validate:"required"`
Description string `yaml:"description" validate:"required"`
AuthRequired []string `yaml:"authRequired"`
Annotations *tools.ToolAnnotations `yaml:"annotations,omitempty"`
}
// validate interface
var _ tools.ToolConfig = Config{}
func (cfg Config) ToolConfigKind() string {
return kind
}
func (cfg Config) Initialize(srcs map[string]sources.Source) (tools.Tool, error) {
// verify source exists
rawS, ok := srcs[cfg.Source]
if !ok {
return nil, fmt.Errorf("no source named %q configured", cfg.Source)
}
// verify the source is compatible
s, ok := rawS.(*lookersrc.Source)
if !ok {
return nil, fmt.Errorf("invalid source for %q tool: source kind must be `looker`", kind)
}
params := parameters.Parameters{}
dashIdParameter := parameters.NewStringParameter("dashboard_id", "The id of the dashboard where this filter will exist")
params = append(params, dashIdParameter)
nameParameter := parameters.NewStringParameter("name", "The name of the Dashboard Filter")
params = append(params, nameParameter)
titleParameter := parameters.NewStringParameter("title", "The title of the Dashboard Filter")
params = append(params, titleParameter)
filterTypeParameter := parameters.NewStringParameterWithDefault("filter_type", "field_filter", "The filter_type of the Dashboard Filter: date_filter, number_filter, string_filter, field_filter (default field_filter)")
params = append(params, filterTypeParameter)
defaultParameter := parameters.NewStringParameterWithRequired("default_value", "The default_value of the Dashboard Filter (optional)", false)
params = append(params, defaultParameter)
modelParameter := parameters.NewStringParameterWithRequired("model", "The model of a field type Dashboard Filter (required if type field)", false)
params = append(params, modelParameter)
exploreParameter := parameters.NewStringParameterWithRequired("explore", "The explore of a field type Dashboard Filter (required if type field)", false)
params = append(params, exploreParameter)
dimensionParameter := parameters.NewStringParameterWithRequired("dimension", "The dimension of a field type Dashboard Filter (required if type field)", false)
params = append(params, dimensionParameter)
multiValueParameter := parameters.NewBooleanParameterWithDefault("allow_multiple_values", true, "The Dashboard Filter should allow multiple values (default true)")
params = append(params, multiValueParameter)
requiredParameter := parameters.NewBooleanParameterWithDefault("required", false, "The Dashboard Filter is required to run dashboard (default false)")
params = append(params, requiredParameter)
annotations := cfg.Annotations
if annotations == nil {
readOnlyHint := false
annotations = &tools.ToolAnnotations{
ReadOnlyHint: &readOnlyHint,
}
}
mcpManifest := tools.GetMcpManifest(cfg.Name, cfg.Description, cfg.AuthRequired, params, annotations)
// finish tool setup
return Tool{
Config: cfg,
Name: cfg.Name,
Kind: kind,
UseClientOAuth: s.UseClientAuthorization(),
AuthTokenHeaderName: s.GetAuthTokenHeaderName(),
Client: s.Client,
ApiSettings: s.ApiSettings,
Parameters: params,
manifest: tools.Manifest{
Description: cfg.Description,
Parameters: params.Manifest(),
AuthRequired: cfg.AuthRequired,
},
mcpManifest: mcpManifest,
}, nil
}
// validate interface
var _ tools.Tool = Tool{}
type Tool struct {
Config
Name string `yaml:"name"`
Kind string `yaml:"kind"`
UseClientOAuth bool
AuthTokenHeaderName string
Client *v4.LookerSDK
ApiSettings *rtl.ApiSettings
AuthRequired []string `yaml:"authRequired"`
Parameters parameters.Parameters `yaml:"parameters"`
manifest tools.Manifest
mcpManifest tools.McpManifest
}
func (t Tool) ToConfig() tools.ToolConfig {
return t.Config
}
func (t Tool) Invoke(ctx context.Context, resourceMgr tools.SourceProvider, params parameters.ParamValues, accessToken tools.AccessToken) (any, error) {
logger, err := util.LoggerFromContext(ctx)
if err != nil {
return nil, fmt.Errorf("unable to get logger from ctx: %s", err)
}
logger.DebugContext(ctx, "params = ", params)
paramsMap := params.AsMap()
dashboard_id := paramsMap["dashboard_id"].(string)
name := paramsMap["name"].(string)
title := paramsMap["title"].(string)
filterType := paramsMap["flter_type"].(string)
switch filterType {
case "date_filter":
case "number_filter":
case "string_filter":
case "field_filter":
default:
return nil, fmt.Errorf("invalid filter type: %s. Must be one of date_filter, number_filter, string_filter, field_filter", filterType)
}
allowMultipleValues := paramsMap["allow_multiple_values"].(bool)
required := paramsMap["required"].(bool)
req := v4.WriteCreateDashboardFilter{
DashboardId: dashboard_id,
Name: name,
Title: title,
Type: filterType,
AllowMultipleValues: &allowMultipleValues,
Required: &required,
}
if v, ok := paramsMap["default_value"]; ok {
if v != nil {
defaultValue := paramsMap["default_value"].(string)
req.DefaultValue = &defaultValue
}
}
if filterType == "field_filter" {
model, ok := paramsMap["model"].(string)
if !ok || model == "" {
return nil, fmt.Errorf("model must be specified for field_filter type")
}
explore, ok := paramsMap["explore"].(string)
if !ok || explore == "" {
return nil, fmt.Errorf("explore must be specified for field_filter type")
}
dimension, ok := paramsMap["dimension"].(string)
if !ok || dimension == "" {
return nil, fmt.Errorf("dimension must be specified for field_filter type")
}
req.Model = &model
req.Explore = &explore
req.Dimension = &dimension
}
sdk, err := lookercommon.GetLookerSDK(t.UseClientOAuth, t.ApiSettings, t.Client, accessToken)
if err != nil {
return nil, fmt.Errorf("error getting sdk: %w", err)
}
resp, err := sdk.CreateDashboardFilter(req, "name", t.ApiSettings)
if err != nil {
return nil, fmt.Errorf("error making create dashboard filter request: %s", err)
}
logger.DebugContext(ctx, "resp = %v", resp)
data := make(map[string]any)
data["result"] = fmt.Sprintf("Dashboard filter \"%s\" added to dashboard %s", *resp.Name, dashboard_id)
return data, nil
}
func (t Tool) ParseParams(data map[string]any, claims map[string]map[string]any) (parameters.ParamValues, error) {
return parameters.ParseParams(t.Parameters, data, claims)
}
func (t Tool) Manifest() tools.Manifest {
return t.manifest
}
func (t Tool) McpManifest() tools.McpManifest {
return t.mcpManifest
}
func (t Tool) Authorized(verifiedAuthServices []string) bool {
return tools.IsAuthorized(t.AuthRequired, verifiedAuthServices)
}
func (t Tool) RequiresClientAuthorization(resourceMgr tools.SourceProvider) bool {
return t.UseClientOAuth
}
func (t Tool) GetAuthTokenHeaderName() string {
return t.AuthTokenHeaderName
}

116
internal/tools/looker/lookeradddashboardfilter/lookeradddashboardfilter_test.go Normal file
View File

@@ -0,0 +1,116 @@
// Copyright 2025 Google LLC
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
package lookeradddashboardfilter_test
import (
"strings"
"testing"
yaml "github.com/goccy/go-yaml"
"github.com/google/go-cmp/cmp"
"github.com/googleapis/genai-toolbox/internal/server"
"github.com/googleapis/genai-toolbox/internal/testutils"
lkr "github.com/googleapis/genai-toolbox/internal/tools/looker/lookeradddashboardfilter"
)
func TestParseFromYamlLookerAddDashboardFilter(t *testing.T) {
ctx, err := testutils.ContextWithNewLogger()
if err != nil {
t.Fatalf("unexpected error: %s", err)
}
tcs := []struct {
desc string
in string
want server.ToolConfigs
}{
{
desc: "basic example",
in: `
tools:
example_tool:
kind: looker-add-dashboard-filter
source: my-instance
description: some description
`,
want: server.ToolConfigs{
"example_tool": lkr.Config{
Name: "example_tool",
Kind: "looker-add-dashboard-filter",
Source: "my-instance",
Description: "some description",
AuthRequired: []string{},
},
},
},
}
for _, tc := range tcs {
t.Run(tc.desc, func(t *testing.T) {
got := struct {
Tools server.ToolConfigs `yaml:"tools"`
}{}
// Parse contents
err := yaml.UnmarshalContext(ctx, testutils.FormatYaml(tc.in), &got)
if err != nil {
t.Fatalf("unable to unmarshal: %s", err)
}
if diff := cmp.Diff(tc.want, got.Tools); diff != "" {
t.Fatalf("incorrect parse: diff %v", diff)
}
})
}
}
func TestFailParseFromYamlLookerAddDashboardFilter(t *testing.T) {
ctx, err := testutils.ContextWithNewLogger()
if err != nil {
t.Fatalf("unexpected error: %s", err)
}
tcs := []struct {
desc string
in string
err string
}{
{
desc: "Invalid method",
in: `
tools:
example_tool:
kind: looker-add-dashboard-filter
source: my-instance
method: GOT
description: some description
`,
err: "unable to parse tool \"example_tool\" as kind \"looker-add-dashboard-filter\": [4:1] unknown field \"method\"\n 1 | authRequired: []\n 2 | description: some description\n 3 | kind: looker-add-dashboard-filter\n> 4 | method: GOT\n ^\n 5 | source: my-instance",
},
}
for _, tc := range tcs {
t.Run(tc.desc, func(t *testing.T) {
got := struct {
Tools server.ToolConfigs `yaml:"tools"`
}{}
// Parse contents
err := yaml.UnmarshalContext(ctx, testutils.FormatYaml(tc.in), &got)
if err == nil {
t.Fatalf("expect parsing to fail")
}
errStr := err.Error()
if !strings.Contains(errStr, tc.err) {
t.Fatalf("unexpected error string: got %q, want substring %q", errStr, tc.err)
}
})
}
}