iflow-mcp_sazboxai_metabase-mcp 0.1.0

A Model Control Protocol (MCP) server that enables AI assistants to interact with Metabase databases and actions

Metabase MCP Server

A Model Control Protocol (MCP) server that enables AI assistants to interact with Metabase databases and actions.

![Metabase MCP Server]

Overview

The Metabase MCP Server provides a bridge between AI assistants and Metabase, allowing AI models to:

• List and explore databases configured in Metabase
• Retrieve detailed metadata about database schemas, tables, and fields
• Visualize relationships between tables in a database
• List and execute Metabase actions
• Perform operations on Metabase data through a secure API

This server implements the [Model Control Protocol (MCP)] specification, making it compatible with AI assistants that support MCP tools.

Features

• Database Exploration: List all databases and explore their schemas
• Metadata Retrieval: Get detailed information about tables, fields, and relationships
• Relationship Visualization: Generate visual representations of database relationships
• Action Management: List, view details, and execute Metabase actions
• Secure API Key Handling: Store API keys encrypted and prevent exposure
• Web Interface: Test and debug functionality through a user-friendly web interface
• Docker Support: Easy deployment with Docker and Docker Compose

Prerequisites

• Metabase instance (v0.46.0 or higher recommended)
• Metabase API key with appropriate permissions
• Docker (for containerized deployment)
• Python 3.10+ (for local development)

Installation

Using Docker (Recommended)

1. Clone this repository:

   git clone https://github.com/yourusername/metabase-mcp.git
   cd metabase-mcp
   

2. Build and run the Docker container:

   docker-compose up -d
   

3. Access the configuration interface at http://localhost:5001

Manual Installation

1. Clone this repository:

   git clone https://github.com/yourusername/metabase-mcp.git
   cd metabase-mcp
   

2. Install dependencies:

   pip install -r requirements.txt
   

3. Run the configuration interface:

   python -m src.server.web_interface
   

4. Access the configuration interface at http://localhost:5000

Configuration

1. Open the web interface in your browser
2. Enter your Metabase URL (e.g., http://localhost:3000)
3. Enter your Metabase API key
4. Click "Save Configuration" and test the connection

Obtaining a Metabase API Key

1. Log in to your Metabase instance as an administrator
2. Go to Settings > Admin settings > API Keys
3. Create a new API key with appropriate permissions
4. Copy the generated key for use in the MCP server

Usage

Running the MCP Server

After configuration, you can run the MCP server:

# Using Docker
docker run -p 5001:5000 metabase-mcp

# Manually
python -m src.server.mcp_server

Available Tools

The MCP server provides the following tools to AI assistants:

1. list_databases: List all databases configured in Metabase
2. get_database_metadata: Get detailed metadata for a specific database
3. db_overview: Get a high-level overview of all tables in a database
4. table_detail: Get detailed information about a specific table
5. visualize_database_relationships: Generate a visual representation of database relationships
6. run_database_query: Execute a SQL query against a database
7. list_actions: List all actions configured in Metabase
8. get_action_details: Get detailed information about a specific action
9. execute_action: Execute a Metabase action with parameters

Testing Tools via Web Interface

The web interface provides a testing area for each tool:

1. List Databases: View all databases configured in Metabase
2. Get Database Metadata: View detailed schema information for a database
3. DB Overview: View a concise list of all tables in a database
4. Table Detail: View detailed information about a specific table
5. Visualize Database Relationships: Generate a visual representation of table relationships
6. Run Query: Execute SQL queries against databases
7. List Actions: View all actions configured in Metabase
8. Get Action Details: View detailed information about a specific action
9. Execute Action: Test executing an action with parameters

Security Considerations

• API keys are stored encrypted at rest
• The web interface never displays API keys in plain text
• All API requests use HTTPS when configured with a secure Metabase URL
• The server should be deployed behind a secure proxy in production environments

Development

Project Structure

metabase-mcp/
├── src/
│   ├── api/            # Metabase API client
│   ├── config/         # Configuration management
│   ├── server/         # MCP and web servers
│   └── tools/          # Tool implementations
├── templates/          # Web interface templates
├── docker-compose.yml  # Docker Compose configuration
├── Dockerfile          # Docker build configuration
├── requirements.txt    # Python dependencies
└── README.md           # Documentation

Adding New Tools

To add a new tool:

1. Implement the tool function in src/tools/
2. Register the tool in src/server/mcp_server.py
3. Add a testing interface in templates/config.html (optional)
4. Add a route in src/server/web_interface.py (if adding a testing interface)

Troubleshooting

Common Issues

• Connection Failed: Ensure your Metabase URL is correct and accessible
• Authentication Error: Verify your API key has the necessary permissions
• Docker Network Issues: When using Docker, ensure proper network configuration

Logs

Check the logs for detailed error information:

# Docker logs
docker logs metabase-mcp

# Manual execution logs
# Logs are printed to the console

Contributing

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