syucream_lightdash-mcp-server

syucream_lightdash-mcp-server

0
databases

The Lightdash MCP Server connects to Lightdash, providing an interface for AI assistants to interact with data using the Model Context Protocol. It offers features to list and retrieve project data, charts, and dashboards.

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.

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

npm install lightdash-mcp-server

Configuration

Create a .env file with your Lightdash API credentials:

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:
npx lightdash-mcp-server
  1. For example usage, check the examples directory. To run the example:
# 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