Custom

About

This project offers a sample implementation for setting up and deploying a custom Model Context Protocol (MCP) server directly on Databricks Apps. It empowers Large Language Models (LLMs) such as Claude and Cursor by enabling them to interact with Databricks and external data sources through a defined set of tools. By integrating with Databricks SQL warehouses, it allows LLMs to execute queries against databases and retrieve real-time stock information, thereby bridging the gap between conversational AI and operational data within the Databricks ecosystem.

Key Features

• Supports seamless deployment to Databricks Apps
• Integrates custom tools for LLMs with Databricks Apps
• Compatible with LLM clients like Claude Desktop and Cursor
• Enables SQL query execution against Databricks SQL warehouses
• Provides a tool for fetching Tokyo Stock Exchange (TSE) stock information
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Use Cases

• Allowing LLMs to retrieve real-time stock market data
• Enabling LLMs to execute SQL queries and fetch data from Databricks SQL warehouses
• Developing and deploying custom LLM-callable tools within the Databricks ecosystem