Lightdash Mcp

Name: Lightdash Mcp
Author: poddubnyoleg

@poddubnyoleg

关于 Lightdash Mcp

MCP server for Lightdash analytics platform. Enables AI assistants like Claude to discover data, execute queries, create charts, and manage dashboards programmatically. Supports Lightdash Cloud and self-hosted instances.

#lightdash #analytics #mcp #claude #business-intelligence #data-visualization #dashboards #python

基本信息

分类

数据与分析

传输方式

stdio

发布者

poddubnyoleg

提交者

配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "lightdash": {
      "command": "uvx",
      "args": [
        "lightdash-mcp"
      ],
      "env": {
        "LIGHTDASH_TOKEN": "<YOUR_TOKEN>",
        "LIGHTDASH_URL": "https://app.lightdash.cloud"
      }
    }
  }
}

工具

未检测到工具

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is Lightdash Mcp?

Lightdash Mcp is a Model Context Protocol (MCP) server that connects AI assistants like Claude and Cursor to Lightdash analytics. It enables LLMs to discover data, create charts, and manage dashboards programmatically.

How to use Lightdash Mcp?

Install via pip install lightdash-mcp, uvx lightdash-mcp, or pipx run lightdash-mcp. Set environment variables LIGHTDASH_TOKEN and LIGHTDASH_URL, then run lightdash-mcp. Optionally configure Cloudflare Access or Google Cloud IAP. Add the server to MCP clients (e.g., Claude Desktop) by providing the command and environment variables.

Key features of Lightdash Mcp

Discovery: explore data catalogs, tables, and schemas
Querying: execute queries with filters, metrics, and aggregations
Chart management: create, read, update, delete charts
Dashboard management: build and manage dashboards with tiles and filters
Resource organization: create and manage spaces for content

Use cases of Lightdash Mcp

Allow an AI assistant to explore available tables and schemas in Lightdash
Automate chart creation and configuration from natural language prompts
Duplicate and modify existing dashboards programmatically
Run ad-hoc metric queries against any explore in a project
Organize analytics content by creating spaces and moving resources

FAQ from Lightdash Mcp

How do I obtain a Lightdash token?

Go to Settings → Personal Access Tokens in your Lightdash instance, click Generate new token, and copy the token (starts with ldt_).

What are the prerequisites?

Python 3.10+, a Lightdash instance (Cloud or self-hosted), and a Lightdash Personal Access Token.

How do I handle authentication errors?

Verify your LIGHTDASH_TOKEN is correct and starts with ldt_, check the token hasn’t expired, and ensure you have the necessary permissions in Lightdash.

How do I set up Google Cloud IAP support?

Install with the [iap] extra (pip install lightdash-mcp[iap]), set IAP_ENABLED=true, and ensure the runtime service account has roles/iam.serviceAccountTokenCreator on itself and roles/iap.httpsResourceAccessor on the Cloud Run service.

How can I add a new tool to the server?

Create a new Python file in lightdash_mcp/tools/ with a TOOL_DEFINITION and a run function. The server automatically discovers and registers the tool on restart.

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