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Metabase MCP server provides integration with the Metabase API, enabling LLM with MCP capabilites to directly interact with your analytics data, this server acts as a bridge between your analytics platform and conversational AI.

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Metabase MCP Server 🚀

A high-performance Model Context Protocol (MCP) server for Metabase, built with FastMCP and Python. This server enables AI assistants like Claude and Cursor to interact seamlessly with your Metabase instance, providing powerful database analytics and visualization capabilities.

✨ Key Features

Database Operations

  • List Databases: Browse all configured Metabase databases
  • Table Discovery: Explore tables with metadata and descriptions
  • Field Inspection: Get detailed field/column information with smart pagination

Query & Analytics

  • SQL Execution: Run native SQL queries with parameter support
  • Card Management: Execute, create, and manage Metabase questions/cards
  • Collection Organization: Create and manage collections for better organization

Authentication & Security

  • API Key Support: Secure authentication via Metabase API keys (recommended)
  • Session-based Auth: Alternative email/password authentication
  • Environment Variables: Secure credential management via .env files

🚀 Quick Start

Prerequisites

  • Python 3.12+
  • Metabase instance with API access
  • uv package manager (recommended) or pip

Installation

Using uv (Recommended)

# Install uv if not already installed
curl -LsSf https://astral.sh/uv/install.sh | sh

# Clone the repository
git clone https://github.com/yourusername/metabase-mcp.git
cd metabase-mcp

# Install dependencies
uv sync

Using pip

# Clone and install
git clone https://github.com/yourusername/metabase-mcp.git
cd metabase-mcp
pip install -r requirements.txt

⚙️ Configuration

Create a .env file with your Metabase credentials:

cp .env.example .env

Configuration Options

Option 1: API Key Authentication (Recommended)

METABASE_URL=https://your-metabase-instance.com
METABASE_API_KEY=your-api-key-here

Option 2: Email/Password Authentication

METABASE_URL=https://your-metabase-instance.com
METABASE_USER_EMAIL=your-email@example.com
METABASE_PASSWORD=your-password

Optional: Custom Host/Port for SSE/HTTP

HOST=localhost  # Default: 0.0.0.0
PORT=9000      # Default: 8000

Usage

Run the Server

# STDIO transport (default)
uv run python server.py

# SSE transport (uses HOST=0.0.0.0, PORT=8000 by default)
uv run python server.py --sse

# HTTP transport (uses HOST=0.0.0.0, PORT=8000 by default)
uv run python server.py --http

# Custom host and port via environment variables
HOST=localhost PORT=9000 uv run python server.py --sse
HOST=192.168.1.100 PORT=8080 uv run python server.py --http

# Set environment variables persistently
export HOST=localhost
export PORT=9000
uv run python server.py --sse

FastMCP CLI Integration

# Run with FastMCP CLI
fastmcp run server.py

# Install as Claude Desktop MCP server
fastmcp install server.py -n "Metabase MCP"

Cursor Integration

For Cursor IDE integration:

STDIO Transport (Default)

uv run python scripts/install-cursor.py

SSE Transport

# Install with SSE transport
uv run python scripts/install-cursor.py --sse        # Port 8000 (default)
uv run python scripts/install-cursor.py --sse 9000   # Custom port

# Or use the dedicated SSE installer
uv run python scripts/install-cursor-sse.py          # Port 8000
uv run python scripts/install-cursor-sse.py 9000     # Custom port

Important for SSE: You must start the server before using Cursor:

uv run python server.py --sse 8000

Claude Integration

After running uv sync, you can find the Python executable at /path/to/repo/.venv/bin/python. To integrate with Claude, add or update the configuration file at ~/Library/Application\ Support/Claude/claude_desktop_config.json:

{
    "mcpServers": {
        "metabase-mcp-server": {
            "command": "/path/to/repo/.venv/bin/python",
            "args": ["/path/to/repo/server.py"]
        }
    }
}

🛠️ Available Tools

Database Operations

Tool Description
list_databases List all configured databases in Metabase
list_tables Get all tables in a specific database with metadata
get_table_fields Retrieve field/column information for a table

Query Operations

Tool Description
execute_query Execute native SQL queries with parameter support
execute_card Run saved Metabase questions/cards

Card Management

Tool Description
list_cards List all saved questions/cards
create_card Create new questions/cards with SQL queries

Collection Management

Tool Description
list_collections Browse all collections
create_collection Create new collections for organization

Transport Methods

The server supports multiple transport methods:

  • STDIO (default): For IDE integration (Cursor, Claude Desktop)
  • SSE: Server-Sent Events for web applications
  • HTTP: Standard HTTP for API access
uv run python server.py                        # STDIO (default)
uv run python server.py --sse                  # SSE (HOST=0.0.0.0, PORT=8000)
uv run python server.py --http                 # HTTP (HOST=0.0.0.0, PORT=8000)
HOST=localhost PORT=9000 uv run python server.py --sse   # Custom host/port

🧪 Development

Setup Development Environment

# Install with dev dependencies
uv sync --group dev

# Or with pip
pip install -r requirements-dev.txt

Code Quality

# Run linting
uv run ruff check .

# Format code
uv run ruff format .

# Type checking
uv run mypy server.py

# Run all tests
uv run pytest -v

# Run with coverage
uv run pytest --cov=server --cov-report=html

Validation

# Validate server setup
uv run python scripts/validate.py

📚 Examples

Query Examples

# List all databases
databases = await list_databases()

# Execute a SQL query
result = await execute_query(
    database_id=1,
    query="SELECT * FROM users LIMIT 10"
)

# Create and run a card
card = await create_card(
    name="Active Users Report",
    database_id=1,
    query="SELECT COUNT(*) FROM users WHERE active = true",
    collection_id=2
)

Example Files

  • examples/quick-start.py - Getting started guide
  • examples/examples.py - Common usage patterns
  • examples/sse-example.py - SSE transport demo

📁 Project Structure

metabase-mcp/
├── server.py                 # Main MCP server implementation
├── pyproject.toml           # Project configuration and dependencies
├── .env.example             # Environment variables template
├── scripts/
│   ├── install-cursor.py    # Cursor IDE installer
│   ├── install-cursor-sse.py # SSE-specific installer
│   └── validate.py          # Installation validator
├── examples/                # Usage examples
├── tests/                   # Test suite
└── docs/                    # Additional documentation

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

📄 License

MIT License - see LICENSE file for details

🔗 Resources

About

Metabase MCP server provides integration with the Metabase API, enabling LLM with MCP capabilites to directly interact with your analytics data, this server acts as a bridge between your analytics platform and conversational AI.

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