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Databricks MCP Server

@JustTryAI

Basic information

Category

Other

Transports

stdio

Author

JustTryAI

About Databricks MCP Server

A Model Completion Protocol (MCP) server for interacting with Databricks services

Databricks MCP Server config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "databricks-mcp-server-justtryai": {
      "command": "uv",
      "args": [
        "venv"
      ]
    }
  }
}

Databricks MCP Server tools

11

List all Databricks clusters

Create a new Databricks cluster

Terminate a Databricks cluster

Get information about a specific Databricks cluster

Start a terminated Databricks cluster

List all Databricks jobs

Run a Databricks job

List notebooks in a workspace directory

Export a notebook from the workspace

List files and directories in a DBFS path

Execute a SQL statement

Overview

What is Databricks MCP Server?

The Databricks MCP Server is a Model Context Protocol (MCP) server that provides access to Databricks functionality via the MCP protocol. It allows LLM-powered tools to interact with Databricks clusters, jobs, notebooks, and more.

How to use Databricks MCP Server?

Install the server using the uv package manager (Python 3.10+ required), set the DATABRICKS_HOST and DATABRICKS_TOKEN environment variables for authentication, then run the provided start script (start_mcp_server.sh on Linux/Mac or start_mcp_server.ps1 on Windows). The server exposes Databricks operations as MCP tools.

Key features of Databricks MCP Server

  • MCP protocol support for LLM interaction with Databricks.
  • Databricks REST API integration for core operations.
  • Tool registration exposing Databricks functionality as MCP tools.
  • Async support built with asyncio for efficient operation.

Use cases of Databricks MCP Server

  • List and manage Databricks clusters (create, terminate, start, get info).
  • Run and list Databricks jobs.
  • Browse and export notebooks from the workspace.
  • List files and directories in a DBFS path.
  • Execute SQL statements on Databricks.

Frequently asked questions

1

What are the prerequisites for using Databricks MCP Server?

Python 3.10 or higher and the `uv` package manager are required. A Databricks workspace with a personal access token is also needed.

2

How do I authenticate with Databricks?

Set the environment variables `DATABRICKS_HOST` (your Databricks instance URL) and `DATABRICKS_TOKEN` (your personal access token). Alternatively, use a `.env` file.

3

What tools does the server expose?

The server exposes tools for clusters (list, create, terminate, get, start), jobs (list, run), notebooks (list, export), files (list in DBFS), and SQL (execute a statement).

4

Does it support running SQL queries?

Yes, the server includes an `execute_sql` tool that can execute a SQL statement.

5

How do I start the server after installation?

Run the wrapper script `start_mcp_server.sh` (Linux/Mac) or `start_mcp_server.ps1` (Windows). The scripts are in the repository root and will start the MCP server ready for connections.

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