databricks-genie-mcp

A server implementing the Model Context Protocol (MCP) to connect with the Databricks Genie API, enabling large language models (LLMs) to ask questions, execute SQL, and interact with Databricks conversational agents.

Features

• Connects to Databricks Genie API as an MCP server
• Lists Genie spaces available in your Databricks workspace (manual/resource-based)
• Fetches metadata (title, description) of specific Genie spaces
• Starts new Genie conversations using natural language questions
• Supports follow-up questions in ongoing Genie conversations
• Retrieves SQL queries and result tables in structured format
• Available MCP tools/functions:
  • get_genie_space_id(): List available Genie space IDs and titles
  • get_space_info(space_id: str): Retrieve title and description of a Genie space
  • ask_genie(space_id: str, question: str): Start a new Genie conversation and get results
  • follow_up(space_id: str, conversation_id: str, question: str): Continue an existing Genie conversation
• Can be integrated with Claude Desktop for conversational data analysis
• Provides Docker support for containerized deployment
• Requires Python 3.7+ and a Databricks workspace with Genie API enabled

Prerequisites

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

Setup

• Clone the repository
• Create and activate a Python virtual environment
• Install dependencies from requirements.txt
• Configure .env file with Databricks credentials
• Manually add Genie space IDs in the code (due to API limitation)
• Optionally test the server with MCP inspector or Docker

Security Considerations

• Keep your .env file secure
• Use tokens with minimal scope and expiration
• Do not expose the server publicly without authentication

License

MIT

Pricing

No pricing information available (open source project).