Metabase MCP Server

@cuenca-mx

Repository

Basic information

About Metabase MCP Server

A Model Context Protocol server that enables interaction with Metabase via LLMs

#metabase #mcp-server #api-integration

Metabase MCP Server config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "metabase-mcp-server-cuenca-mx": {
      "command": "uv",
      "args": [
        "run",
        "pytest"
      ]
    }
  }
}

Metabase MCP Server tools

Tool list not available yet

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We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is Metabase MCP Server?

An MCP server that exposes Metabase API functionality through the Model Context Protocol interface, enabling AI assistants to interact with Metabase cards, databases, collections, and queries. It is designed for users who want to combine Metabase analytics with AI-driven workflows.

How to use Metabase MCP Server?

Clone the repository and configure your AI assistant client (Claude, Cursor, etc.) with the provided JSON object. Set the command to uv, point directory to the project folder, and supply METABASE_URL and METABASE_API_KEY in the environment variables. The server then exposes tools that your assistant can call.

Key features of Metabase MCP Server

List Metabase cards
List available databases
Execute queries on existing cards
Run arbitrary queries
Create new cards
Create bookmarks and list collections

Use cases of Metabase MCP Server

Allow an AI assistant to retrieve and present data from Metabase cards.
Let users run ad‑hoc queries on Metabase databases via natural language.
Automate the creation of new cards and bookmarks in Metabase.
Explore and browse collections and database schemas without leaving the chat interface.

Frequently asked questions

What are the runtime requirements?

Python 3.12 or higher and the `uv` package manager.

How do I configure authentication?

Set the environment variables `METABASE_URL` (your Metabase instance URL) and `METABASE_API_KEY` (a valid API key) in the MCP server configuration.

How can I test or debug the server?

Use the MCP Inspector by running `make dev`, or run unit tests with `uv run pytest`.

How do I set up the MCP server in my AI client?

Add the provided JSON block to your client’s MCP server settings, replacing the absolute path and environment values with your own.

Comments

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