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Builds and deploys a custom Model Context Protocol server on Databricks Apps, providing two LLM-callable tools for data interaction.
关于
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.
主要功能
- 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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使用案例
- 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
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