Files
genai-toolbox/docs/en/resources/sources/mindsdb.md
Yuan Teoh 293c1d6889 feat!: update configuration file v2 (#2369)
This PR introduces a significant update to the Toolbox configuration
file format, which is one of the primary **breaking changes** required
for the implementation of the Advanced Control Plane.

# Summary of Changes
The configuration schema has been updated to enforce resource isolation
and facilitate atomic, incremental updates.
* Resource Isolation: Resource definitions are now separated into
individual blocks, using a distinct structure for each resource type
(Source, Tool, Toolset, etc.). This improves readability, management,
and auditing of configuration files.
* Field Name Modification: Internal field names have been modified to
align with declarative methodologies. Specifically, the configuration
now separates kind (general resource type, e.g., Source) from type
(specific implementation, e.g., Postgres).

# User Impact
Existing tools.yaml configuration files are now in an outdated format.
Users must eventually update their files to the new YAML format.

# Mitigation & Compatibility
Backward compatibility is maintained during this transition to ensure no
immediate user action is required for existing files.
* Immediate Backward Compatibility: The source code includes a
pre-processing layer that automatically detects outdated configuration
files (v1 format) and converts them to the new v2 format under the hood.
* [COMING SOON] Migration Support: The new toolbox migrate subcommand
will be introduced to allow users to automatically convert their old
configuration files to the latest format.

# Example
Example for config file v2:
```
kind: sources
name: my-pg-instance
type: cloud-sql-postgres
project: my-project
region: my-region
instance: my-instance
database: my_db
user: my_user
password: my_pass
---
kind: authServices
name: my-google-auth
type: google
clientId: testing-id
---
kind: tools
name: example_tool
type: postgres-sql
source: my-pg-instance
description: some description
statement: SELECT * FROM SQL_STATEMENT;
parameters:
- name: country
  type: string
  description: some description
---
kind: tools
name: example_tool_2
type: postgres-sql
source: my-pg-instance
description: returning the number one
statement: SELECT 1;
---
kind: toolsets
name: example_toolset
tools:
- example_tool
```

---------

Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
Co-authored-by: Averi Kitsch <akitsch@google.com>
2026-01-27 16:58:43 -08:00

6.7 KiB

title, type, weight, description
title type weight description
MindsDB docs 1 MindsDB is an AI federated database that enables SQL queries across hundreds of datasources and ML models.

About

MindsDB is an AI federated database in the world. It allows you to combine information from hundreds of datasources as if they were SQL, supporting joins across datasources and enabling you to query all unstructured data as if it were structured.

MindsDB translates MySQL queries into whatever API is needed - whether it's REST APIs, GraphQL, or native database protocols. This means you can write standard SQL queries and MindsDB automatically handles the translation to APIs like Salesforce, Jira, GitHub, email systems, MongoDB, and hundreds of other datasources.

MindsDB also enables you to use ML frameworks to train and use models as virtual tables from the data in those datasources. With MindsDB, the GenAI Toolbox can now expand to hundreds of datasources and leverage all of MindsDB's capabilities on ML and unstructured data.

Key Features:

  • Federated Database: Connect and query hundreds of datasources through a single SQL interface
  • Cross-Datasource Joins: Perform joins across different datasources seamlessly
  • API Translation: Automatically translates MySQL queries into REST APIs, GraphQL, and native protocols
  • Unstructured Data Support: Query unstructured data as if it were structured
  • ML as Virtual Tables: Train and use ML models as virtual tables
  • MySQL Wire Protocol: Compatible with standard MySQL clients and tools

Supported Datasources

MindsDB supports hundreds of datasources, including:

Business Applications

  • Salesforce: Query leads, opportunities, accounts, and custom objects
  • Jira: Access issues, projects, workflows, and team data
  • GitHub: Query repositories, commits, pull requests, and issues
  • Slack: Access channels, messages, and team communications
  • HubSpot: Query contacts, companies, deals, and marketing data

Databases & Storage

  • MongoDB: Query NoSQL collections as structured tables
  • Redis: Key-value stores and caching layers
  • Elasticsearch: Search and analytics data
  • S3/Google Cloud Storage: File storage and data lakes

Communication & Email

  • Gmail/Outlook: Query emails, attachments, and metadata
  • Slack: Access workspace data and conversations
  • Microsoft Teams: Team communications and files
  • Discord: Server data and message history

Example Queries

Cross-Datasource Analytics

-- Join Salesforce opportunities with GitHub activity
SELECT 
    s.opportunity_name,
    s.amount,
    g.repository_name,
    COUNT(g.commits) as commit_count
FROM salesforce.opportunities s
JOIN github.repositories g ON s.account_id = g.owner_id
WHERE s.stage = 'Closed Won'
GROUP BY s.opportunity_name, s.amount, g.repository_name;

Email & Communication Analysis

-- Analyze email patterns with Slack activity
SELECT 
    e.sender,
    e.subject,
    s.channel_name,
    COUNT(s.messages) as message_count
FROM gmail.emails e
JOIN slack.messages s ON e.sender = s.user_name
WHERE e.date >= '2024-01-01'
GROUP BY e.sender, e.subject, s.channel_name;

ML Model Predictions

-- Use ML model to predict customer churn
SELECT 
    customer_id,
    customer_name,
    predicted_churn_probability,
    recommended_action
FROM customer_churn_model
WHERE predicted_churn_probability > 0.8;

Requirements

Database User

This source uses standard MySQL authentication since MindsDB implements the MySQL wire protocol. You will need to create a MindsDB user to login to the database with. If MindsDB is configured without authentication, you can omit the password field.

Example

kind: sources
name: my-mindsdb-source
type: mindsdb
host: 127.0.0.1
port: 3306
database: my_db
user: ${USER_NAME}
password: ${PASSWORD} # Optional: omit if MindsDB is configured without authentication
queryTimeout: 30s # Optional: query timeout duration

Working Configuration Example

Here's a working configuration that has been tested:

kind: sources
name: my-pg-source
type: mindsdb
host: 127.0.0.1
port: 47335
database: files
user: mindsdb

{{< notice tip >}} Use environment variable replacement with the format ${ENV_NAME} instead of hardcoding your secrets into the configuration file. {{< /notice >}}

Use Cases

With MindsDB integration, you can:

  • Query Multiple Datasources: Connect to databases, APIs, file systems, and more through a single SQL interface
  • Cross-Datasource Analytics: Perform joins and analytics across different data sources
  • ML Model Integration: Use trained ML models as virtual tables for predictions and insights
  • Unstructured Data Processing: Query documents, images, and other unstructured data as structured tables
  • Real-time Predictions: Get real-time predictions from ML models through SQL queries
  • API Abstraction: Write SQL queries that automatically translate to REST APIs, GraphQL, and native protocols

Reference

field type required description
type string true Must be "mindsdb".
host string true IP address to connect to (e.g. "127.0.0.1").
port string true Port to connect to (e.g. "3306").
database string true Name of the MindsDB database to connect to (e.g. "my_db").
user string true Name of the MindsDB user to connect as (e.g. "my-mindsdb-user").
password string false Password of the MindsDB user (e.g. "my-password"). Optional if MindsDB is configured without authentication.
queryTimeout string false Maximum time to wait for query execution (e.g. "30s", "2m"). By default, no timeout is applied.

Resources