# 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](https://nodejs.org/) 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.
2. Add the required inputs for your [instance](https://docs.cloud.google.com/looker/docs/set-up-and-administer-looker) 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](https://learn.microsoft.com/en-us/microsoft-365/security/defender-endpoint/configure-exclusions-microsoft-defender-antivirus?view=o365-worldwide) 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.
```bash
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):
```json
{
"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](https://cloud.google.com/looker).