MCP Server

The set of servers and tools in this repo is fluid and will evolve over time. We welcome contributions to this repo - please first read the

Local serverstdioPython

What is the MCP MCP server?

If you already use MCP, the mcp mcp server is the piece that lets your assistant work with it directly. The set of servers and tools in this repo is fluid and will evolve over time. We welcome contributions to this repo - please first read the contributor guidelines to streamline the process and discover areas where help.

What the server does

An experimental collection of MCP servers to help AI agents fetch enterprise data from Databricks, automate common developer actions on Databricks, etc:

Installation

Setup follows the usual MCP pattern — install or clone the server, register it in your client's configuration file, restart the client. The configuration blocks on this page cover the common clients.

Available tools

The toolset is worth reading before you wire it up, because it tells you what the integration is really for:

  • Overview — The Overview tool exposed by this server

Worth knowing first

  • It runs with your machine's permissions. That is convenient and also the reason to think about what you point it at before you approve a tool call.
  • Keep per-call confirmation enabled while you learn its behaviour; it is the cheapest safeguard you have.

Where it fits

This sits in the developer tooling group, where several servers overlap in what they claim to do but differ sharply once you actually set them up. MCP's toolset — Overview — is a fair guide to whether it matches your workflow. It is maintained by databrickslabs; worth a glance at recent repository activity before you build anything load-bearing on it.

This entry was verified against MCP's own documentation before publication; SyncDev keeps the directory reviewed rather than auto-generated.

Available tools

ToolWhat it does
OverviewThe Overview tool exposed by this server.

How to install the MCP MCP server

{
  "mcpServers": {
    "databricks_unity_catalog": {
      "command": "/path/to/uv/executable/uv",
      "args": [
        "--directory",
        "/path/to/this/repo",
        "run",
        "unitycatalog-mcp",
        "-s",
        "your_catalog.your_schema",
        "-g",
        "genie_space_id_1,genie_space_id_2"
      ]
    }
  }
}

Configuration as documented by the project. Restart the client after saving.

Example prompts to try

  • Use MCP to Overview.

Frequently asked questions

It connects MCP to MCP-compatible AI assistants such as Claude and Cursor, exposing 1 tool (Overview) that the assistant can call on your behalf. Instead of copying data back and forth by hand, the assistant works with MCP directly.