Metabase MCP Server
A Model Context Protocol (MCP) server for Metabase that gives AI assistants full access to your analytics platform — dashboards, cards, databases, tables, collections, and more.
Developed and maintained by EaseCloud — cloud-native, AI-driven, and data infrastructure solutions.
Quick Start
export METABASE_URL=https://your-metabase-instance.com
export METABASE_API_KEY=your_metabase_api_key
npx @easecloudio/mcp-metabase-server
96 Tools Available
Supported Metabase Versions
- Metabase v0.46.x and above (recommended: v0.48.x or later)
- Metabase Cloud (fully supported)
- Self-hosted instances (Docker, JAR, or cloud deployments)
Installation
npx (Recommended)
npx @easecloudio/mcp-metabase-server
Global install
npm install -g @easecloudio/mcp-metabase-server
mcp-metabase-server
Docker
docker build -t mcp-metabase-server .
docker run -it --rm \
-e METABASE_URL=https://your-metabase-instance.com \
-e METABASE_API_KEY=your_metabase_api_key \
mcp-metabase-server
Configuration
Authentication
API Key (preferred):
METABASE_URL=https://your-metabase-instance.com
METABASE_API_KEY=your_metabase_api_key
Username / Password (fallback):
METABASE_URL=https://your-metabase-instance.com
METABASE_USERNAME=your_username
METABASE_PASSWORD=your_password
Copy .env.example to .env and fill in your values.
Tool Filtering (TOOL_MODE)
Set TOOL_MODE to control which tools are exposed to the AI. Useful for limiting surface area or preventing accidental writes.
TOOL_MODE=essential # smallest surface area
TOOL_MODE=read # read-only
TOOL_MODE=all # everything (default)
Claude Desktop Integration
MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%/Claude/claude_desktop_config.json
Using npx:
{
"mcpServers": {
"metabase": {
"command": "npx",
"args": ["@easecloudio/mcp-metabase-server"],
"env": {
"METABASE_URL": "https://your-metabase-instance.com",
"METABASE_API_KEY": "your_metabase_api_key"
}
}
}
}
With tool filtering:
{
"mcpServers": {
"metabase": {
"command": "npx",
"args": ["@easecloudio/mcp-metabase-server"],
"env": {
"METABASE_URL": "https://your-metabase-instance.com",
"METABASE_API_KEY": "your_metabase_api_key",
"TOOL_MODE": "essential"
}
}
}
}
Using a local build:
{
"mcpServers": {
"metabase": {
"command": "node",
"args": ["/path/to/metabase-server/dist/index.js"],
"env": {
"METABASE_URL": "https://your-metabase-instance.com",
"METABASE_API_KEY": "your_metabase_api_key"
}
}
}
}
Username / password fallback:
{
"mcpServers": {
"metabase": {
"command": "npx",
"args": ["@easecloudio/mcp-metabase-server"],
"env": {
"METABASE_URL": "https://your-metabase-instance.com",
"METABASE_USERNAME": "your_username",
"METABASE_PASSWORD": "your_password"
}
}
}
}
Available Tools
Core CRUD
Card Layout
Public Sharing & Embedding
Revision, Audit & Discovery
Core CRUD
Execution & Export
Parameters
Metadata & Discovery
Public Sharing & Embedding
Core CRUD
Querying
Schema & Sync
Diagnostics
Metadata
Card Virtual Tables
Management
CSV Upload (Metabase-managed tables)
Collections
Users
Permissions
Search
These tools enable an AI to convert native SQL questions into interactive MBQL questions. Metabase has no REST API for this conversion — it requires field IDs, which these tools cache locally.
How it works:
get_card— extract the SQL anddatabase_idget_schema_cache— get tables + field IDs for MBQL references like["field", 42, null]- AI translates SQL → MBQL using the cached field IDs
create_card— save the new interactive question
Cache is stored at ~/.easecloud/metabase-mcp/cache/{url-hash}/ with a 24-hour TTL and scoped per Metabase instance.
MCP Resources
Access Metabase entities directly via metabase:// URIs:
Development
npm install
npm run build # compile TypeScript → dist/
npm run watch # incremental rebuild
npm run dev # build + start
npm run inspector # launch MCP Inspector for debugging
Debugging
MCP servers communicate over stdio, which makes direct debugging awkward. Use the MCP Inspector:
npm run inspector
The Inspector provides a browser UI for sending tool calls and inspecting responses.
About EaseCloud
EaseCloud is a cloud consulting and solutions company specializing in:
- Cloud-native application development
- AI & automation integrations
- DevOps and infrastructure management
- Data analytics and BI platform consulting
We built this project to contribute to the open-source MCP ecosystem while demonstrating our expertise in integration, automation, and cloud solutions.
If your team is adopting Metabase at scale or looking to integrate AI with your BI stack, get in touch — we provide consulting, customization, and managed support for enterprises.
📧 [email protected] 🌐 easecloud.io
Bug Reports & Issues
Found a bug or have a feature request?
Please include:
- Metabase version
- MCP server version
- Steps to reproduce
- Expected vs actual behavior
- Any error messages or logs
Contributing
Contributions are welcome. Visit the GitHub repository to submit issues or pull requests.
License
MIT — see LICENSE for details.