databricks-genie-MCP

A Model Context Protocol (MCP) server that connects to the Databricks Genie API, allowing LLMs to ask natural language questions, run SQL queries, and interact with Databricks conversational agents.

• List Genie spaces available in your Databricks workspace (Currently Manual/Using Resource)
• Fetch metadata (title, description) of a specific Genie space
• Start new Genie conversations with natural language questions
• Ask follow-up questions in ongoing Genie conversations
• Retrieve SQL and result tables in structured format

• Python 3.7+
• Databricks workspace with:
• Personal access token
• Genie API enabled
• Permissions to access Genie spaces and run queries

1. Clone this repository

1. Create and activate a virtual environment (recommended):

 python -m venv .venv
 source .venv/bin/activate

Install dependencies:

pip install -r requirements.txt

Create a .env file in the root directory with the following variables:

DATABRICKS_HOST=your-databricks-instance.cloud.databricks.com # Don't add https
DATABRICKS_TOKEN=your-personal-access-token

📌 Manually Adding Genie Space IDs

Note: At this time, the Databricks Genie API does not provide a public endpoint to list all available space IDs and titles. (afaik) As a workaround, you need to manually add the Genie space IDs and their titles in the get_genie_space_id() function in main.py.

You can test the MCP server using the inspector (optional but recommended):

npx @modelcontextprotocol/inspector python main.py

OR

You can directly build and run docker to test the server

Download Claude Desktop

Install Your MCP Server: From your project directory, run:

mcp install main.py

Once Server Installed

1. Connect in Claude

1. Open Claude Desktop

1. Click Resour