lightdash-mcp-server

A MCP(Model Context Protocol) server that accesses to Lightdash.

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:

npx -y @smithery/cli install lightdash-mcp-server --client claude

Manual Installation

npm install lightdash-mcp-server

Configuration

• LIGHTDASH_API_KEY: Your Lightdash PAT
• LIGHTDASH_API_URL: The API base URL

Usage

1. Start the MCP server.

Directly:

npx lightdash-mcp-server

Or, run the installed module with node.

2. Edit your MCP configuration json:

...
    "lightdash": {
      "command": "npx",
      "args": [
        "-y",
        "lightdash-mcp-server"
      ],
      "env": {
        "LIGHTDASH_API_KEY": "<your PAT>",
        "LIGHTDASH_API_URL": "https://<your base url>"
      }
    },
...

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