# mcp-databricks-server

> MCP Server

This repository provides a Model Context Protocol (MCP) server that connects to Databricks, enabling LLMs to execute SQL queries, list jobs, retrieve job statuses, and access detailed job information.

## Overview

- **Category:** AI
- **Language:** Python
- **Stars:** 50
- **Forks:** 1
- **Owner:** JordiNeil
- **GitHub:** https://github.com/JordiNeil/mcp-databricks-server
- **Created:** 2025-03-21T02:54:04+00:00
- **Updated:** 2025-03-25T08:46:03+00:00
- **Source:** https://model-context-protocol.com/servers/mcp-server-databricks-model-context-protocol

## Setup

## Setup

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
   ```

## Tools

## Available Tools

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