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lightdash-mcp-server

by MCP-Mirror

IntegrationLightdashAPIData Analytics

This server provides MCP-compatible access to Lightdash's API, allowing AI assistants to interact with your Lightdash data through a standardized interface. It acts as a bridge between AI models and Lightdash analytics.

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Last updated: N/A

What is lightdash-mcp-server?

lightdash-mcp-server is a Model Context Protocol (MCP) server that enables access to Lightdash, a business intelligence tool. It allows AI assistants to interact with Lightdash data through a standardized MCP interface.

How to use lightdash-mcp-server?

  1. Install the server using npm install lightdash-mcp-server. 2. Configure your Lightdash API credentials in a .env file. 3. Start the server using npx lightdash-mcp-server. 4. Use the provided examples to interact with the server.

Key features of lightdash-mcp-server

  • MCP-compatible access to Lightdash

  • List projects, spaces, charts, and dashboards

  • Get details of specific projects

  • Retrieve custom metrics and catalog information

  • Get charts and dashboards as code

Use cases of lightdash-mcp-server

  • Enabling AI assistants to query Lightdash data

  • Integrating Lightdash data into AI-powered applications

  • Automating data analysis tasks using AI

  • Building custom AI-driven dashboards and reports

FAQ from lightdash-mcp-server

What is MCP?

MCP stands for Model Context Protocol. It's a standardized interface for AI models to interact with external data sources.

What is Lightdash?

Lightdash is a business intelligence tool that allows you to explore and visualize your data.

How do I get a Lightdash API key?

You can obtain a Lightdash API key from your Lightdash account settings.

What versions of Lightdash are supported?

The server is designed to work with the Lightdash API v1, and should be compatible with most Lightdash cloud and self-hosted instances.

How can I contribute to the project?

You can contribute by forking the repository, creating a feature branch, running tests and linting, and submitting a pull request.