A MCP (Model Context Protocol) server that accesses to Lightdash, providing MCP-compatible access to Lightdash's API, allowing AI assistants to interact with Lightdash data through a standardized interface.
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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 @syucream/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

Features

projects
spaces
charts
dashboards
metrics
catalog
code

Category

Integrations