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Spring AI Example

Demonstrates Spring AI tools implementation with an MCP server and agentic AI proposals.

About

This project showcases practical implementation patterns and best practices for utilizing Spring AI tools, featuring an Model Context Protocol (MCP) server with both WebFlux and WebMvc SSE support, and an agentic AI proposal module, illustrating methods as tools, custom result converters, tool context, and tool parameters.

Key Features

  • Implements Model Context Protocol (MCP) server with WebFlux and WebMvc SSE support
  • Supports custom tool result converters
  • Includes examples of tool parameter annotation with @ToolParam
  • Demonstrates using methods as tools with the @Tool annotation
  • Provides a ToolContext parameter for accessing contextual information
  • 0 GitHub stars

Use Cases

  • Building AI-powered proposal generation systems
  • Creating real-time update systems using SSE with Spring AI
  • Implementing custom tool integrations within Spring AI applications