A high-performance Model Context Protocol (MCP) server for Metabase, enabling AI assistants like Claude, Cursor, and other MCP clients to interact seamlessly with your Metabase instance. Query databases, execute SQL, manage dashboards, and automate analytics workflows with natural language through AI-powered database operations.
Perfect for: Data analysts, developers, and teams looking to integrate AI assistants with their Metabase business intelligence platform for automated SQL queries, dashboard management, and data exploration.
- 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
- SQL Execution: Run native SQL queries with parameter support and templating
- Card Management: Execute, create, and manage Metabase questions/cards
- Collection Organization: Create and manage collections for better organization
- Natural Language Queries: Let AI assistants translate questions into SQL
- API Key Support: Secure authentication via Metabase API keys (recommended)
- Session-based Auth: Alternative email/password authentication
- Environment Variables: Secure credential management via
.envfiles
- Claude Desktop: Native integration with Anthropic's Claude AI
- Cursor IDE: Seamless integration for AI-assisted development
- Any MCP Client: Compatible with all Model Context Protocol clients
- Context-aware Logging: Real-time logging with debug, info, warning, and error levels visible to AI clients
- Proper Error Handling: FastMCP
ToolErrorexceptions for better error messages and debugging - Middleware Stack: Built-in error handling and logging middleware for production reliability
- Best Practices: Follows latest FastMCP patterns with duplicate prevention and clean configuration
- Modern Python: Uses Python 3.12+ type hints (
|syntax) for better type safety
- Python 3.12+
- Metabase instance with API access
uvxoruvpackage manager
# Run directly without installing (like npx for Python)
uvx metabase-mcp
# With environment variables
METABASE_URL=https://your-instance.com METABASE_API_KEY=your-key uvx metabase-mcp# Install globally
uv tool install metabase-mcp
# Or with pip
pip install metabase-mcp
# Then run
metabase-mcp# Clone the repository
git clone https://github.com/cheukyin175/metabase-mcp.git
cd metabase-mcp
# Install dependencies
uv sync
# Run the server
uv run python server.pyCreate a .env file with your Metabase credentials:
cp .env.example .envMETABASE_URL=https://your-metabase-instance.com
METABASE_API_KEY=your-api-key-hereMETABASE_URL=https://your-metabase-instance.com
METABASE_USER_EMAIL=your-email@example.com
METABASE_PASSWORD=your-passwordHOST=localhost # Default: 0.0.0.0
PORT=9000 # Default: 8000# Run directly with uvx
uvx metabase-mcp
# With custom Metabase instance
METABASE_URL=https://your-instance.com METABASE_API_KEY=your-key uvx metabase-mcp# 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 --httpYou can manually configure Cursor by editing your Cursor settings.
For SSE transport: You must start the server before using Cursor:
uv run python server.py --sseAdd this to ~/Library/Application Support/Claude/claude_desktop_config.json:
{
"mcpServers": {
"metabase-mcp": {
"command": "uvx",
"args": ["metabase-mcp"],
"env": {
"METABASE_URL": "https://your-metabase-instance.com",
"METABASE_API_KEY": "your-api-key-here"
}
}
}
}If you've cloned the repository:
{
"mcpServers": {
"metabase-mcp": {
"command": "uv",
"args": [
"run",
"--directory",
"/absolute/path/to/metabase-mcp",
"python",
"server.py"
],
"env": {
"METABASE_URL": "https://your-metabase-instance.com",
"METABASE_API_KEY": "your-api-key-here"
}
}
}
}fastmcp install server.py -n "Metabase MCP"| 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 |
| Tool | Description |
|---|---|
execute_query |
Execute native SQL queries with parameter support |
execute_card |
Run saved Metabase questions/cards |
| Tool | Description |
|---|---|
list_cards |
List all saved questions/cards |
create_card |
Create new questions/cards with SQL queries |
| Tool | Description |
|---|---|
list_collections |
Browse all collections |
create_collection |
Create new collections for organization |
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# Install with dev dependencies
uv sync --group dev
# Or with pip
pip install -r requirements-dev.txt# Run linting
uv run ruff check .
# Format code
uv run ruff format .
# Type checking
uv run mypy server.py# 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
)metabase-mcp/
├── server.py # Main MCP server implementation
├── pyproject.toml # Project configuration and dependencies
└── .env.example # Environment variables template
Contributions are welcome! Please feel free to submit a Pull Request.
MIT License - see LICENSE file for details
- FastMCP Documentation
- Model Context Protocol
- Metabase API Documentation
- Claude Desktop Documentation
- Cursor IDE
metabase mcp model-context-protocol claude cursor ai-assistant fastmcp sql database analytics business-intelligence bi data-analysis anthropic llm python automation api data-science query-builder natural-language-sql
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- Natural Language Database Queries: Ask Claude to query your Metabase databases using plain English
- Automated Report Generation: Use AI to create and manage Metabase cards and collections
- Data Exploration: Let AI assistants help you discover insights from your data
- SQL Query Assistance: Get help writing and optimizing SQL queries through AI
- Dashboard Management: Automate the creation and organization of Metabase dashboards
- Data Analysis Workflows: Integrate AI-powered analytics into your development workflow