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Demonstrates Spring AI's integration with Model Context Protocol (MCP) for building Spring Boot applications with server and client functionalities.

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About

This project showcases how to integrate Spring AI's support for MCP (Model Context Protocol) within Spring Boot applications, covering both server-side and client-side implementations. It provides a practical example of using Spring AI to build MCP servers that offer their capabilities to LLMs, using services like Geocoder and Timezone to respond to prompts for geographical data.

Key Features

  • Integrates Spring AI with MCP for streamlined contextual AI interactions.
  • Offers a console interface for interacting with an LLM using MCP clients.
  • Provides Spring Boot starters for MCP client and server implementations.
  • 2 GitHub stars
  • Includes Geocoder and Timezone services as example MCP-enabled tools.
  • Uses Llama3.2 via Ollama to support the use of TOOLS within the model.

Use Cases

  • Demonstrating MCP client-server communication within a Spring Boot environment.
  • Building AI assistants that leverage external data sources through MCP.
  • Integrating geographical information services into LLM-based applications.