{"type":"mcp_server","name":"mcp-databricks-server","description":"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.","category":"AI","language":"Python","stars":50,"forks":1,"owner":"JordiNeil","github_url":"https://github.com/JordiNeil/mcp-databricks-server","homepage":null,"setup":"## Setup\n\n1. Clone this repository\n2. Create and activate a virtual environment (recommended):\n   ```\n   python -m venv .venv\n   source .venv/bin/activate  # On Windows: .venv\\Scripts\\activate\n   ```\n3. Install dependencies:\n   ```\n   pip install -r requirements.txt\n   ```\n4. Create a `.env` file in the root directory with the following variables:\n   ```\n   DATABRICKS_HOST=your-databricks-instance.cloud.databricks.com\n   DATABRICKS_TOKEN=your-personal-access-token\n   DATABRICKS_HTTP_PATH=/sql/1.0/warehouses/your-warehouse-id\n   ```\n5. Test your connection (optional but recommended):\n   ```\n   python test_connection.py\n   ```","tools":"## Available Tools\n\n1. run_sql_query(sql: str) - Execute SQL queries on your Databricks SQL warehouse\n2. list_jobs() - List all Databricks jobs in your workspace\n3. get_job_status(job_id: int) - Get the status of a specific Databricks job by ID\n4. get_job_details(job_id: int) - Get detailed information about a specific Databricks job","faq":null,"created_at":"2025-03-21T02:54:04+00:00","updated_at":"2025-03-25T08:46:03+00:00","source_url":"https://model-context-protocol.com/servers/mcp-server-databricks-model-context-protocol","related_articles":[]}