genai-toolbox/docs/LOOKER_README.md

Looker MCP Server

The Looker Model Context Protocol (MCP) Server gives AI-powered development tools the ability to work with your Looker instance. It supports exploring models, running queries, managing dashboards, and more.

Features

An editor configured to use the Looker MCP server can use its AI capabilities to help you:

• Explore Models - Get models, explores, dimensions, measures, filters, and parameters
• Run Queries - Execute Looker queries, generate SQL, and create query URLs
• Manage Dashboards - Create, run, and modify dashboards
• Manage Looks - Search for and run saved looks
• Health Checks - Analyze instance health and performance

Prerequisites

• Node.js installed.
• Access to a Looker instance.
• API Credentials (Client ID and Client Secret) or OAuth configuration.

Install & Configuration

1. In the Antigravity MCP Store, click the "Install" button.

   Note

   On first use, the installation process automatically downloads and uses MCP Toolbox >=0.26.0. To update MCP Toolbox, use: npm i -g @toolbox-sdk/server@latest To always run the latest version, update the MCP server configuration to use: npx -y @toolbox-sdk/server@latest --prebuilt looker.

2. Add the required inputs for your instance in the configuration pop-up, then click "Save". You can update this configuration at any time in the "Configure" tab.

You'll now be able to see all enabled tools in the "Tools" tab.

Note

If you encounter issues with Windows Defender blocking the execution, you may need to configure an allowlist. See Configure exclusions for Microsoft Defender Antivirus for more details.

Usage

Once configured, the MCP server will automatically provide Looker capabilities to your AI assistant. You can:

• "Find explores in the 'ecommerce' model."
• "Run a query to show total sales by month."
• "Create a new dashboard named 'Sales Overview'."

Server Capabilities

The Looker MCP server provides a wide range of tools. Here are some of the key capabilities:

Tool Name	Description
get_models	Retrieves the list of LookML models.
get_explores	Retrieves the list of explores defined in a LookML model.
query	Run a query against the LookML model.
query_sql	Generate the SQL that Looker would run.
run_look	Runs a saved look.
run_dashboard	Runs all tiles in a dashboard.
make_dashboard	Creates a new dashboard.
add_dashboard_element	Adds a tile to a dashboard.
health_pulse	Checks the status of the Looker instance.
dev_mode	Toggles development mode.
get_projects	Lists LookML projects.

Custom MCP Server Configuration

The MCP server is configured using environment variables.

export LOOKER_BASE_URL="<your-looker-instance-url>"  # e.g. `https://looker.example.com`. You may need to add the port, i.e. `:19999`.
export LOOKER_CLIENT_ID="<your-looker-client-id>"
export LOOKER_CLIENT_SECRET="<your-looker-client-secret>"
export LOOKER_VERIFY_SSL="true" # Optional, defaults to true
export LOOKER_SHOW_HIDDEN_MODELS="true" # Optional, defaults to true
export LOOKER_SHOW_HIDDEN_EXPLORES="true" # Optional, defaults to true
export LOOKER_SHOW_HIDDEN_FIELDS="true" # Optional, defaults to true

Add the following configuration to your MCP client (e.g., settings.json for Gemini CLI, mcp_config.json for Antigravity):

{
  "mcpServers": {
    "looker": {
      "command": "npx",
      "args": ["-y", "@toolbox-sdk/server", "--prebuilt", "looker", "--stdio"],
      "env": {
        "LOOKER_BASE_URL": "https://your.looker.instance.com",
        "LOOKER_CLIENT_ID": "your-client-id",
        "LOOKER_CLIENT_SECRET": "your-client-secret"
      }
    }
  }
}

Documentation

For more information, visit the Looker documentation.