Spring AI Example MCP Server

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lucasdengcn

关于 Spring AI Example MCP Server

spring ai example. mcp server, agentic ai.

#spring#springai#mcp-server

Spring AI Example MCP Server 配置

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该服务器的 README 中没有可解析的 MCP 配置块，请前往代码仓库查看安装说明。

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Spring AI Example MCP Server 工具

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工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is Spring AI Example?

This project demonstrates implementation patterns and best practices for using Spring AI tools, integrating with the Model Context Protocol (MCP) through a server module (with WebFlux and WebMvc SSE support) and a client module for building AI-powered proposals. It is designed for developers working with Spring AI, MCP, and large language models.

How to use Spring AI Example?

Clone the repository and run the Spring Boot application. Configure the Ollama AI model, PGVector vector store, and H2 database in the application properties. The mcp-server module can be invoked via SSE endpoints, while the proposal-agent module acts as an MCP client.

Key features of Spring AI Example

Methods as tools via @Tool annotation
Custom tool result converters
Tool context injection in methods
Tool parameter descriptions with @ToolParam
MCP server with SSE support
MCP client for AI proposal generation

Use cases of Spring AI Example

Building chatbots that retrieve current date/time or customer information
Creating proposal generation systems with tool-based data access
Demonstrating Spring AI tool patterns in an MCP architecture
Testing real-time SSE updates from MCP servers

常见问题

What is the project structure?

It contains two main modules: `mcp-server` (MCP server with SSE support) and `proposal-agent` (MCP client for AI proposals), plus a common source folder.

What AI model and database are used?

The configuration uses the Ollama AI model with PGVector for vector storage and H2 database for development.

What transport does the MCP server use?

It uses Server-Sent Events (SSE) for real‑time communication, implemented with Spring’s `SseEmitter`.

How are tools defined in Spring AI?

Methods are annotated with `@Tool` to become tools, optionally using `@ToolParam` for parameter descriptions and custom result converters via `resultConverter`.

Does the project include client and server examples?

Yes, the `mcp-server` module implements the MCP server, while the `proposal-agent` module implements the MCP client.

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