Databricks Genie MCP
D

Databricks Genie MCP

This project implements a Model Context Protocol (MCP) server, exposing the Databricks Genie API functionality as a tool. It supports querying Databricks data in natural language and can be integrated with MCP clients such as Claude Desktop.
2 points
9.4K

What is the Databricks Genie MCP service?

This service transforms the Genie AI assistant functionality of Databricks into a standardized MCP tool, allowing you to interact with AI assistants like Claude in natural language to query information in the Databricks data warehouse. You can obtain data insights in everyday language without writing SQL.

How to use the Genie MCP service?

Simply configure the service path in clients that support the MCP protocol, such as Claude Desktop, and you can query data through conversations. For example, ask 'How much were our DBU consumption last month?' and the system will automatically convert it into an SQL query and return the results.

Use cases

It is suitable for scenarios where business personnel need to quickly obtain data insights, monitor system usage, audit data access records, etc., and do not want to write SQL for frequent queries. It is particularly suitable for ad - hoc data exploration and analysis needs.

Main features

Natural language query
You can obtain data by asking questions in everyday English or Chinese without learning SQL syntax.
Conversation management
Supports creating and managing multi - turn conversation contexts to maintain query coherence.
Intelligent SQL generation
Automatically converts natural language into optimized SQL queries.
Result retrieval
Supports retrieving complete query results or summary reports.
Advantages
Zero - code data analysis, reducing the technical threshold
Real - time connection to the Databricks data warehouse, with accurate and reliable results
Supports progressive clarification of complex queries and multi - turn conversations
Integrated with the enterprise - level security system, with fine - grained permission control
Limitations
Databricks workspace administrators need to pre - configure access permissions
Professional data teams may still need to be involved in complex analyses
Query performance is limited by Genie and SQL warehouse resources

How to use

Environment preparation
Ensure that Python 3.10+ and the Databricks CLI are installed, and obtain workspace access permissions.
Configure authentication
Create a.env file in the working directory to set Databricks authentication information.
Client configuration
Add the MCP server configuration in the Claude Desktop settings, specifying the Python interpreter and script path.
Start querying
Use the tool icon in the Claude chat window to select the Genie function or ask questions in natural language.

Usage examples

Resource usage monitoring
Business managers want to know the team's resource consumption.
Data security audit
The security team checks sensitive data access records.

Frequently Asked Questions

Why can't Claude Desktop find the Genie tool?
What should I do if the query returns a permission error?
How to improve the query response speed?

Related resources

Genie MCP technical blog
Detailed technical implementation principles and use - case analyses.
Claude Desktop download
Official MCP client application.
MCP protocol specification
Technical standard document for the Model Context Protocol.

Installation

Copy the following command to your Client for configuration
Note: Your key is sensitive information, do not share it with anyone.

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