Metabase MCP Server
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.
Details
- Transport
- SSE
- License
- MIT
Explore
- List databases, explore tables, and inspect fields with metadata
- Execute native SQL queries with parameter support and templating
- Execute MongoDB queries with automatic JSON conversion
- Run, create, and manage Metabase cards/questions
- Create and organize collections for better data organization
- Secure authentication via API keys or email/password
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
Metabase MCP ServerCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
- Python 3.12+
- Metabase instance with API access
- uvx or uv package manager
- 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
uvx metabase-mcp
METABASE_URL=https://your-instance.com METABASE_API_KEY=your-key uvx metabase-mcp
uv tool install metabase-mcp
uv sync
METABASE_URL=https://your-metabase-instance.com
METABASE_API_KEY=your-api-key-here
METABASE_URL=https://your-metabase-instance.com
[email protected]
METABASE_PASSWORD=your-password
HOST=localhost PORT=9000 uv run python server.py --sse
HOST=192.168.1.100 PORT=8080 uv run python server.py --http
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"
}
}
}
}
```bash
uv sync --group dev
list_dashboards
List all dashboards in Metabase
list_cards
List all questions/cards in Metabase
list_databases
List all databases in Metabase
execute_card
Execute a Metabase question/card and get results
get_dashboard_cards
Get all cards in a dashboard
execute_query
Execute a SQL query against a Metabase database
create_card
Create a new question/card in Metabase
update_card_visualization
Update visualization settings for a card
add_card_to_dashboard
Add a card to a dashboard
create_dashboard
Create a new dashboard in Metabase
list_collections
List all collections in Metabase
create_collection
Create a new collection in Metabase
list_tables
List all tables in a database
get_table_fields
Get all fields/columns in a table
update_dashboard
Update an existing dashboard
delete_dashboard
Delete a dashboard
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"metabase mcp server": {
"metabase-mcp": {
"command": "uvx",
"args": [
"metabase-mcp"
]
}
}
}
}McpServers
{
"metabase-mcp": {
"command": "uvx",
"args": [
"metabase-mcp"
]
}
}
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.
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 paginationQuery & Analytics
- SQL Execution: Run native SQL queries with parameter support and templating - MongoDB Support: Execute native MongoDB queries with automatic JSON conversion for aggregation pipelines - Card Management: Execute, create, and manage Metabase questions/cards (SQL and MongoDB) - Collection Organization: Create and manage collections for better organization - Natural Language Queries: Let AI assistants translate questions into SQL or MongoDB queriesAuthentication & 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
AI Assistant Integration
- 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 clientsEnhanced Performance & Reliability
- Context-aware Logging: Real-time logging with debug, info, warning, and error levels visible to AI clients - Proper Error Handling: FastMCPToolError exceptions 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
Quick Start
Prerequisites
- Python 3.12+ - Metabase instance with API access -uvx or uv package manager
Installation
Option 1: Using uvx (Easiest - No Installation Required)
```bashSign in to leave a review
Use Google, GitHub, or an email account so ratings stay tied to real people.
No reviews posted yet.
