How to Install Databricks MCP in Gemini CLI

Official Databricks integration — run notebooks, manage clusters, and query lakehouse data through AI

What Databricks MCP does

The official Databricks MCP server gives AI agents access to lakehouse analytics and data engineering workflows. It can run notebooks, inspect clusters, and query Delta tables. Features: - Execute notebooks and review job results - Query Delta Lake and Unity Catalog tables - Manage clusters and compute resources - Inspect data lineage and table schemas - Run SQL analytics and generate dashboards - Access MLflow model registry and experiments Databricks MCP is built for data teams who want AI to take action on analytics, ML, and lakehouse assets.

databricks

analytics

lakehouse

sql

data-engineering

Installation steps

1Copy the config below
2Open ~/.gemini/settings.json
3Paste inside "mcpServers": {}
4Restart Gemini CLI

Configuration

File location: ~/.gemini/settings.json

settings.jsonjson

{
  "databricksMcp": {
    "command": "npx",
    "args": [
      "-y",
      "@databricks/mcp"
    ],
    "env": {
      "DATABRICKS_HOST": "https://adb-...",
      "DATABRICKS_TOKEN": "..."
    }
  }
}

Full server details Open Config Editor

Install in other clients

🤖Claude Desktop 💻Claude Code ⌨️Cursor 🏄Windsurf ✨OpenAI

For maintainers

If you maintain Databricks MCP, add this badge to your README to show it's verified on CuratedMCP:

[![CuratedMCP Verified](https://curatedmcp.com/api/badge/databricks-mcp)](https://curatedmcp.com/marketplace/databricks-mcp)

Related servers

PostgreSQL MCP

Natural language SQL queries on your PostgreSQL databases

Free

SQLite MCP Server

SQLite database queries, analysis, and memo storage for local AI workflows

Free

Snowflake MCP

Official Snowflake integration — query data, manage warehouses, and inspect pipelines through AI

Free