🚀 MCP Databricks
About
My Databricks MCP server to interact with Databricks through LLM models
Details
- Author
- leminkhoa
- Downloads
- 343
- Categories
- Other
Jump to
- Manage Databricks clusters (create, start, delete, list)
- Execute Python, Scala, and SQL commands on clusters
- Install libraries (JAR, WHL, PyPI, Maven, CRAN)
- Manage SQL warehouses (list, create)
- Manipulate workspace objects (import, delete, create directories)
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
🚀 MCP DatabricksCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
Clone the repository, create a .env file with your DATABRICKS_HOST and DATABRICKS_TOKEN, then run the server using Docker (recommended for production) or locally with uv. Configure it in Cursor via mcp.json or connect directly to any MCP client (e.g., Claude Desktop) using stdio transport.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"\ud83d\ude80 mcp databricks": {
"databricks-mcp": {
"command": "docker",
"args": [
"build",
"-t",
"databricks-mcp",
"."
]
}
}
}
}McpServers
{
"databricks-mcp": {
"command": "docker",
"args": [
"build",
"-t",
"databricks-mcp",
"."
]
}
}🚀 MCP Databricks
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</div>
<p align="center">
<b>A powerful Databricks integration for AI assistants via Model Context Protocol</b>
</p>
📖 Introduction
MCP Databricks seamlessly connects AI assistants to your Databricks workspaces through the Model Context Protocol (MCP). Built with Python, it provides a rich collection of tools for managing virtually every aspect of your Databricks environment.
With this server, AI assistants like Claude can:
- 🔧 Manage compute resources with precision
- 📊 Execute SQL queries and analyze results
- 📁 Organize and manipulate workspace objects
- ✨ And much more!
🔍 Prerequisites
- 🐍 Python 3.11 or higher
- 💻 A Databricks workspace
- 🔑 Databricks Personal Access Token (PAT)
- 📦 Required Python packages (installed in setup)
🚀 Quickstart
1️⃣ Clone the repository
git clone https://github.com/leminkhoa/databricks-mcp
cd databricks-mcp
2️⃣ Configure environment variables
Create a .env file in the project root with your Databricks credentials:
```ini
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