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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
14

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 queryYou can obtain data by asking questions in everyday English or Chinese without learning SQL syntax.
Conversation managementSupports creating and managing multi - turn conversation contexts to maintain query coherence.
Intelligent SQL generationAutomatically converts natural language into optimized SQL queries.
Result retrievalSupports retrieving complete query results or summary reports.

Advantages and limitations

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 monitoringBusiness managers want to know the team's resource consumption.
Data security auditThe 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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