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Works with

Claude CodeClaude DesktopCursorVS CodeClineCodex CLIOpenClaw+ any MCP client

Install to Claude Code

This server doesn't publish a one-line install command. Follow the setup in the source repository.

Summary

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

README.md

Databricks Genie MCP Server

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.

✨ Features

  • 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

🧱 Prerequisites

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

⚙️ Setup

  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.

🧪 Test the Server

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

💬 Use with Claude Desktop

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 Resources → Add Resource
  1. Select your Genie MCP Server
  1. Start chatting with your data using natural language! 🎯

🧾 Obtaining Databricks Credentials

Host Your Databricks instance URL (e.g., your-instance.cloud.databricks.com) — do not include https://

Token

  1. Go to your Databricks workspace
  1. Click your username (top right) → User Settings
  2. Under the Developer tab, click Manage under "Access tokens"
  3. Generate a new token and copy it

🚀 Running the Server

python main.py

This will start the Genie MCP server over the stdio transport for LLM interaction.

🧰 Available MCP Tools

The following MCP tools are available:

Tool Description

  1. get_genie_space_id() List available Genie space IDs and titles
  2. get_space_info(space_id: str) Retrieve title and description of a Genie space
  3. ask_genie(space_id: str, question: str) Start a new Genie conversation and get results
  4. follow_up(space_id: str, conversation_id: str, question: str) Continue an existing Genie conversation

🛠️ Troubleshooting

Common Issues

  • Invalid host: Ensure the host does not include https://
  • Token error: Make sure your personal access token is valid and has access to Genie
  • Timeout: Check if the Genie space is accessible and not idle/expired
  • No data returned: Ensure your query is valid for the selected space

🔐 Security Considerations

  • Keep your .env file secure and never commit it to version control
  • Use minimal scope tokens with expiration whenever possible
  • Avoid exposing this server in public-facing environments unless authenticated

Claude Desktop Screenshots

!image

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