Model Context Protocol server for Databricks (local development)
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# Databricks MCP Server (Local) Complete setup and configuration for the Databricks MCP (Model Context Protocol) server integration with Cursor IDE. This repository provides a full MCP server implementation with setup scripts, configuration templates, and comprehensive documentation. ## Overview The Databricks MCP server enables AI assistants in Cursor IDE to interact with your Databricks workspace using natural language. You can manage notebooks, clusters, jobs, SQL warehouses, and workspace files—all through conversational queries. ## Features - **Notebook Management**: Run, list, get, create, and delete notebooks - **Cluster Management**: List, create, start, stop, and restart clusters - **Job Management**: Create, run, monitor, and manage Databricks jobs - **SQL Warehouses**: Execute SQL queries and manage SQL warehouses - **Workspace Operations**: List, read, create, and delete workspace files - **Git Repositories**: List and manage Git repositories in workspace ## Quick Start ### Prerequisites - Python 3.9 or higher - Cursor IDE - A Databricks workspace account - Basic familiarity with command-line operations ### Installation Steps 1. **Install Dependencies** ```bash ./scripts/install-dependencies.sh ``` This will check for Python and install `uv` (the recommended package manager) if needed. 2. **Run Setup Script** ```bash ./scripts/setup.sh ``` This interactive script will: - Guide you through creating a Databricks Personal Access Token - Create your `.env` file with credentials - Generate a Cursor MCP configuration file 3. **Install the MCP Server** ```bash pip install -e . ``` Or if using `uvx`: ```bash uvx databricks-mcp-server-local ``` 4. **Configure Cursor IDE** - Open Cursor Settings - Navigate to **Features > MCP Servers** - Click **"+ Add new global MCP server"** - Copy the configuration from `config/cursor-mcp-config.json` (created by setup script) - Or manually add t…
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