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MCP server · AI

lightdash-server

A MCP(Model Context Protocol) server that accesses to lightdash( https://www.lightdash.com/ )

Unclaimed ai
39Low

Scored 5 months ago · breakdown

About lightdash-server

lightdash-server is an MCP server published by git+syucream in the AI category: a MCP(Model Context Protocol) server that accesses to lightdash( https://www.lightdash.com/ ).

Install

Install
npx lightdash-mcp-server
Claude Code
claude mcp add lightdash-mcp-server-gitsyucr -- npx -y lightdash-mcp-server
npx
npx -y lightdash-mcp-server

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

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Security checks

  • ✓README presentThe repository ships documentation.
  • !Scoped permissionsDoesn't declare a permission scope. Assume it can do anything its process can.

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README

lightdash-mcp-server

smithery badge npm version

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 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

The lightdash-mcp-server supports two transport modes: Stdio (default) and HTTP.

Stdio Transport (Default)

  1. Start the MCP server:
npx lightdash-mcp-server
  1. 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>"
      }
    },
...

HTTP Transport (Streamable HTTP)

  1. Start the MCP server in HTTP mode:
npx lightdash-mcp-server -port 8080

This starts the server using StreamableHTTPServerTransport, making it accessible via HTTP at http://localhost:8080/mcp.

  1. Configure your MCP client to connect via HTTP:

For Claude Desktop and other MCP clients:

Edit your MCP configuration json to use the url field instead of command and args:

...
    "lightdash": {
      "url": "http://localhost:8080/mcp"
    },
...

For programmatic access:

Use the streamable HTTP client transport:

import { Client } from '@modelcontextprotocol/sdk/client/index.js';
import { StreamableHTTPClientTransport } from '@modelcontextprotocol/sdk/client/streamableHttp.js';

const client = new Client({
  name: 'my-client',
  version: '1.0.0'
}, {
  capabilities: {}
});

const transport = new StreamableHTTPClientTransport(
  new URL('http://localhost:8080/mcp')
);

await client.connect(transport);

Note: When using HTTP mode, ensure the environment variables LIGHTDASH_API_KEY and LIGHTDASH_API_URL are set in the environment where the server is running, as they cannot be passed through MCP client configuration.

See examples/list_spaces_http.ts for a complete example of connecting to the HTTP server programmatically.

Development

Available Scripts

  • npm run dev - Start the server in development mode with hot reloading (stdio transport)
  • npm run dev:http - Start the server in development mode with HTTP transport on port 8080
  • 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

README copy captured when this server was indexed; it may lag the repository. The original is authoritative.

Questions

About lightdash-server

How do I install lightdash-server?

Run npx lightdash-mcp-server, then add the server to your MCP client's configuration.

Is lightdash-server safe to use with an AI agent?

Its trust score is 39 out of 100 (low). It passes 1 of the 2 static security checks run so far; the failures are listed above. It has no ConduID identity yet, so agent calls to it are not receipted.

Is lightdash-server still maintained?

Conduid hasn't recorded a commit date for this repository yet. Check the repository directly for recent activity.