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JordiNeil/mcp-databricks-server: MCP Server for Databricks

A Model Context Protocol (MCP) server that connects to Databricks API, allowing LLMs to run SQL queries, list jobs, and get job status.

  1. Clone this repository
  2. Create and activate a virtual environment (recommended):
    python -m venv .venv
    source .venv/bin/activate  # On Windows: .venv\Scripts\activate
    
  3. Install dependencies:
    pip install -r requirements.txt
    
  4. Create a .env file in the root directory with the following variables:
    DATABRICKS_HOST=your-databricks-instance.cloud.databricks.com
    DATABRICKS_TOKEN=your-personal-access-token
    DATABRICKS_HTTP_PATH=/sql/1.0/warehouses/your-warehouse-id
    
  5. Test your connection (optional but recommended):
    python test_connection.py
    
Obtaining Databricks Credentials
  1. Host: Your Databricks instance URL (e.g., your-instance.cloud.databricks.com)
  2. Token: Create a personal access token in Databricks:
  3. HTTP Path: For your SQL warehouse:

Start the MCP server:

You can test the MCP server using the inspector by running

npx @modelcontextprotocol/inspector python3 main.py

The following MCP tools are available:

  1. run_sql_query(sql: str) - Execute SQL queries on your Databricks SQL warehouse
  2. list_jobs() - List all Databricks jobs in your workspace
  3. get_job_status(job_id: int) - Get the status of a specific Databricks job by ID
  4. get_job_details(job_id: int) - Get detailed information about a specific Databricks job

When used with LLMs that support the MCP protocol, this server enables natural language interaction with your Databricks environment:


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