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

Installing via Smithery

To install Lightdash MCP Server for Claude Desktop automatically via Smithery:

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

Manual 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

2. 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