Lightdash MCP Server

# lightdash-mcp-server [](https://smithery.ai/server/@syucream/lightdash-mcp-server) A [MCP(Model Context Protocol)](https://www.anthropic.com/news/model-context-protocol) server that accesses to [Lightdash](https://www.lightdash.com/). This server provides MCP-compatible access to Lightdash's API, allowing AI assistants to interact with your Lightdash data through a standardized interface. <a href="https://glama.ai/mcp/servers/e1gbb6sflq"> <img width="380" height="200" src="https://glama.ai/mcp/servers/e1gbb6sflq/badge" alt="Lightdash Server MCP server" /> </a> ## Features Available tools: - `list_projects` - List all projects in the Lightdash organization - `get_project` - Get details of a specific project - `list_spaces` - List all spaces in a project - `list_charts` - List all charts in a project - `list_dashboards` - List all dashboards in a project - `get_custom_metrics` - Get custom metrics for a project - `get_catalog` - Get catalog for a project - `get_metrics_catalog` - Get metrics catalog for a project - `get_charts_as_code` - Get charts as code for a project - `get_dashboards_as_code` - Get dashboards as code for a project ## Quick Start ### Installation #### Installing via Smithery To install Lightdash MCP Server for Claude Desktop automatically via [Smithery](https://smithery.ai/server/@syucream/lightdash-mcp-server): ```bash npx -y @smithery/cli install @syucream/lightdash-mcp-server --client claude ``` #### Manual Installation ```bash npm install lightdash-mcp-server ``` ### Configuration Create a `.env` file with your Lightdash API credentials: ```env LIGHTDASH_API_KEY=your_api_key LIGHTDASH_API_URL=https://app.lightdash.cloud/api/v1 # or your custom Lightdash instance URL ``` ### Usage 1. Start the MCP server: ```bash npx lightdash-mcp-server ``` 2. For example usage, check the `examples` directory. To run the example: ```bash # Set required environment variables export EXAMPLES_CLIENT_LIGHTDASH_API_KEY=your_api_key export EXAMPLES_CLIENT_LIGHTDASH_PROJECT_UUID=your_project_uuid # Run the example npm run examples ``` ## Development ### Available Scripts - `npm run dev` - Start the server in development mode with hot reloading - `npm run build` - Build the project for production - `npm run start` - Start the production server - `npm run lint` - Run linting checks (ESLint and Prettier) - `npm run fix` - Automatically fix linting issues - `npm run examples` - Run the example scripts ### Contributing 1. Fork the repository 2. Create your feature branch 3. Run tests and linting: `npm run lint` 4. Commit your changes 5. Push to the branch 6. Create a Pull Request