Lightdash

v1.0.0Analyticsstable

mcp server for lightdash

analyticsbusiness-intelligenceclaudedata-visualizationlightdash
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What is Lightdash?

Lightdash is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to mcp server for lightdash

mcp server for lightdash

This server falls under the Analytics category on MCPgee, the world's largest MCP server directory with 33,000+ servers.

Features

  • mcp server for lightdash

Use Cases

Business intelligence dashboards
Data visualization and analytics
poddubnyoleg

Maintainer

LicenseMIT
Languagepython
Versionv1.0.0
UpdatedApr 17, 2026
Statushealthy
Maintenanceactive

Works with

ClaudeOpenAIwindowsmacoslinux

Installation

Manual Installation

npx lightdash-mcp

Configuration

Configuration Details

Config File

claude_desktop_config.json

Performance

Response Metrics

Response Time< 200ms
ThroughputMedium

Resource Usage

Memory UsageLow
CPU UsageLow

How to Set Up and Use Lightdash

Lightdash MCP is a Python-based Model Context Protocol server that connects AI assistants like Claude and Cursor to your Lightdash business intelligence instance, enabling them to discover data catalogs, run queries, create charts, and manage dashboards through natural language. The server exposes over 30 tools covering the full analytics workflow — from exploring table schemas and executing metric queries to building dashboard tiles and managing spaces. Teams running Lightdash on cloud or self-hosted infrastructure can use this server to let AI agents answer ad-hoc data questions, automate report creation, and update dashboards without requiring BI tool expertise.

Prerequisites

  • Python 3.10 or higher
  • A Lightdash instance (cloud at app.lightdash.cloud or self-hosted)
  • A Lightdash Personal Access Token (generated from Lightdash Settings > Personal Access Tokens, starts with 'ldt_')
  • The Lightdash project UUID (optional; falls back to the first available project if not set)
  • An MCP client such as Claude Desktop or Claude Code
1

Install lightdash-mcp

Install the package from PyPI using pip, pipx, or use uvx to run it directly without permanent installation.

pip install lightdash-mcp
# or with pipx:
pipx install lightdash-mcp
# or run directly with uvx:
uvx lightdash-mcp
2

Get your Lightdash Personal Access Token

Log into your Lightdash instance, navigate to Settings > Personal Access Tokens, and click 'Generate new token'. Copy the token — it starts with 'ldt_'.

3

Find your Lightdash project UUID

In Lightdash, go to your project settings or look at the URL when viewing a project — the UUID is the alphanumeric string in the path (e.g., /projects/3fc2835f-...). This is optional; the server falls back to the first available project.

4

Configure your MCP client

Add lightdash-mcp to your claude_desktop_config.json or equivalent config file. The LIGHTDASH_TOKEN and LIGHTDASH_URL variables are required.

{
  "mcpServers": {
    "lightdash": {
      "command": "uvx",
      "args": ["lightdash-mcp"],
      "env": {
        "LIGHTDASH_TOKEN": "ldt_your_token_here",
        "LIGHTDASH_URL": "https://app.lightdash.cloud",
        "LIGHTDASH_PROJECT_UUID": "your-project-uuid"
      }
    }
  }
}
5

Verify the connection

Restart your MCP client and ask it to list Lightdash projects or explores. If connected correctly, it will return your project and table names.

Lightdash Examples

Client configuration

Claude Desktop configuration using uvx to run lightdash-mcp with your Lightdash cloud credentials.

{
  "mcpServers": {
    "lightdash": {
      "command": "uvx",
      "args": ["lightdash-mcp"],
      "env": {
        "LIGHTDASH_TOKEN": "ldt_your_token_here",
        "LIGHTDASH_URL": "https://app.lightdash.cloud",
        "LIGHTDASH_PROJECT_UUID": "3fc2835f-0000-0000-0000-000000000000"
      }
    }
  }
}

Prompts to try

Example prompts for exploring data, querying metrics, and building dashboards with Lightdash.

- "List all available explores and tables in my Lightdash project"
- "Show me the schema for the 'orders' explore including all dimensions and metrics"
- "Run a query on the orders table showing total revenue by month for the last 6 months"
- "Create a new chart showing daily active users over the past 30 days and add it to the 'Growth' dashboard"
- "List all dashboards in the project and show me the tiles in the 'Executive Summary' dashboard"

Troubleshooting Lightdash

Authentication error: 401 Unauthorized

Verify that LIGHTDASH_TOKEN is set correctly and has not expired. Personal Access Tokens can expire — regenerate one in Lightdash Settings > Personal Access Tokens. Also ensure LIGHTDASH_URL matches your actual instance URL exactly (no trailing slash).

Tools return empty results or 'project not found'

If LIGHTDASH_PROJECT_UUID is not set, the server uses the first available project. To target a specific project, find its UUID in the Lightdash URL or project settings and set LIGHTDASH_PROJECT_UUID in the env block.

Connection error when behind Google Cloud IAP

Install the IAP extra: 'pip install lightdash-mcp[iap]'. Then set IAP_ENABLED=true in your environment. If using user credentials (ADC), also set IAP_SA to your service account email. The runtime service account needs roles/iap.httpsResourceAccessor on the Cloud Run service.

Frequently Asked Questions about Lightdash

What is Lightdash?

Lightdash is a Model Context Protocol (MCP) server that mcp server for lightdash It connects AI assistants to external tools and data sources through a standardized interface.

How do I install Lightdash?

Follow the installation instructions on the Lightdash GitHub repository. Clone the repo, install dependencies, and add the server config to your AI client.

Which AI clients work with Lightdash?

Lightdash works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.

Is Lightdash free to use?

Yes, Lightdash is open source and available under the MIT license. You can use it freely in both personal and commercial projects.

Browse More Analytics MCP Servers

Explore all analytics servers available in the MCPgee directory. Each server includes setup guides for Claude, Cursor, and VS Code.

Quick Config Preview

{ "mcpServers": { "lightdash-mcp": { "command": "npx", "args": ["-y", "lightdash-mcp"] } } }

Add this to your claude_desktop_config.json or .cursor/mcp.json

Read the full setup guide →

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