databricks-mcp
MCP Databricks integrates AI assistants with Databricks through the Model Context Protocol, providing advanced tools for managing Databricks environments. It supports resource management, SQL query execution, and workspace organization, enhancing productivity for AI-assisted data tasks.
🚀 MCP Databricks
A powerful Databricks integration for AI assistants via Model Context Protocol
📖 Introduction
MCP Databricks seamlessly connects AI assistants to your Databricks workspaces through the Model Context Protocol (MCP). Built with Python, it offers tools for managing Databricks environments, including compute resources, SQL query execution, and workspace organization.
🔍 Prerequisites
- Python 3.11 or higher
- A Databricks workspace
- Databricks Personal Access Token (PAT)
🚀 Quickstart
- Clone the repository and configure environment variables.
- Choose installation via Docker or local installation with
uv.
🚀 Usage
The MCP server can be run using Docker or uv, and it connects to MCP clients like Claude Desktop using stdio transport.
🧰 Tools and Capabilities
Includes cluster management, library management, command execution, SQL warehouse management, and workspace object management.