模型上下文协议（Model Context Protocol）

<dependency>
    <groupId>org.springframework.experimental</groupId>
    <artifactId>spring-ai-mcp</artifactId>
    <version>0.2.0</version>
</dependency>

dependencies {
    implementation 'org.springframework.experimental:spring-ai-mcp:0.2.0'
}

<repositories>
  <repository>
    <id>spring-milestones</id>
    <name>Spring Milestones</name>
    <url>https://repo.spring.io/libs-milestone-local</url>
    <snapshots>
      <enabled>false</enabled>
    </snapshots>
  </repository>
</repositories>

var stdioParams = ServerParameters.builder("npx")
        .args("-y", "@modelcontextprotocol/server-brave-search")
        .addEnvVar("BRAVE_API_KEY", System.getenv("BRAVE_API_KEY"))
        .build();

var mcpClient = McpClient.using(new StdioClientTransport(stdioParams)).sync();

var init = mcpClient.initialize();

var chatClient = chatClientBuilder
        .defaultFunctions(mcpClient.listTools(null)
                .tools()
                .stream()
                .map(tool -> new McpFunctionCallback(mcpClient, tool))
                .toArray(McpFunctionCallback[]::new))
        .build();

String response = chatClient
        .prompt("Does Spring AI supports the Model Context Protocol? Please provide some references.")
        .call().content();

// List<McpFunctionCallback> functionCallbacks;
var chatClient = chatClientBuilder.defaultFunctions(functionCallbacks).build();

@Bean
public List<McpFunctionCallback> functionCallbacks(McpSyncClient mcpClient) {
    // 获取MCP服务器中的工具列表
    return mcpClient.listTools(null)
            // 将每个工具转换为Function Callback
            .tools()
            .stream()
            .map(tool -> new McpFunctionCallback(mcpClient, tool))
            .toList();
}

@Bean(destroyMethod = "close")
public McpSyncClient mcpClient() {
    // 配置服务器启动参数
    var stdioParams = ServerParameters.builder("npx")
            .args("-y", "@modelcontextprotocol/server-filesystem", "path"))
            .build(); // 1

    // 创建同步MCP客户端
    var mcpClient = McpClient.sync(new StdioServerTransport(stdioParams),
            Duration.ofSeconds(10), new ObjectMapper()); //2

    // 初始化客户端连接
    var init = mcpClient.initialize(); // 3
    System.out.println("MCP Initialized: " + init);

    return mcpClient;
}

USER: 所有商品的价格总和是多少
ASSISTANT: 所有商品的价格总和是1642.8元。

USER: 告诉我价格高于平均值的商品
ASSISTANT:
以下是价格高于平均值的商品：

1. Smart Watch，价格为 199.99 元
2. Wireless Earbuds，价格为 89.99 元
3. Mini Drone，价格为 299.99 元
4. Keyboard，价格为 129.99 元
5. Gaming Headset，价格为 159.99 元
6. Fitness Tracker，价格为 119.99 元
7. Portable SSD，价格为 179.99 元

@Bean(destroyMethod = "close")
public McpSyncClient mcpClient() {

    var stdioParams = ServerParameters.builder("uvx")
            .args("mcp-server-sqlite", "--db-path", getDbPath())
            .build();

    var mcpClient = McpClient.sync(new StdioServerTransport(stdioParams),
            Duration.ofSeconds(10), new ObjectMapper());

    var init = mcpClient.initialize();

    System.out.println("MCP Initialized: " + init);

    return mcpClient;
}

@Bean
public List<McpFunctionCallback> functionCallbacks(McpSyncClient mcpClient) {
    return mcpClient.listTools(null)
            .tools()
            .stream()
            .map(tool -> new McpFunctionCallback(mcpClient, tool))
            .toList();
}

<!-- 添加Spring AI MCP starter依赖 -->
<dependency>
   <groupId>org.springframework.ai</groupId>
   <artifactId>spring-ai-mcp-client-spring-boot-starter</artifactId>
</dependency>

spring:
  ai:
    dashscope:
      # 配置通义千问API密钥
      api-key: ${DASH_SCOPE_API_KEY}
    mcp:
      client:
        stdio:
          # 指定MCP服务器配置文件路径（推荐）
          servers-configuration: classpath:/mcp-servers-config.json
          # 直接配置示例，和上边的配制二选一
          # connections:
          #   server1:
          #     command: java
          #     args:
          #       - -jar
          #       - /path/to/your/mcp-server.jar

{
    "mcpServers": {
        // 定义名为"weather"的MCP服务器
        "weather": {
            // 指定启动命令为java
            "command": "java",
            // 定义启动参数
            "args": [
                "-Dspring.ai.mcp.server.stdio=true",
                "-Dspring.main.web-application-type=none",
                "-jar",
                "/path/to/your/mcp-server.jar"
            ],
            // 环境变量配置（可选）
            "env": {}
        }
    }
}

@SpringBootApplication
public class Application {

    public static void main(String[] args) {
        // 启动Spring Boot应用
        SpringApplication.run(Application.class, args);
    }

    @Bean
    public CommandLineRunner predefinedQuestions(
            ChatClient.Builder chatClientBuilder,
            ToolCallbackProvider tools,
            ConfigurableApplicationContext context) {
        return args -> {
            // 构建ChatClient并注入MCP工具
            var chatClient = chatClientBuilder
                    .defaultTools(tools)
                    .build();

            // 定义用户输入
            String userInput = "北京的天气如何？";
            // 打印问题
            System.out.println("\n>>> QUESTION: " + userInput);
            // 调用LLM并打印响应
            System.out.println("\n>>> ASSISTANT: " +
                chatClient.prompt(userInput).call().content());

            // 关闭应用上下文
            context.close();
        };
    }
}

<dependency>
   <groupId>org.springframework.ai</groupId>
   <artifactId>spring-ai-mcp-client-webflux-spring-boot-starter</artifactId>
</dependency>

spring:
  ai:
    dashscope:
      api-key: ${DASH_SCOPE_API_KEY}
    mcp:
      client:
        sse:
          connections:
            server1:
              url: http://localhost:8080

@SpringBootApplication
public class Application {

    public static void main(String[] args) {
        SpringApplication.run(Application.class, args);
    }

    @Bean
    public CommandLineRunner predefinedQuestions(ChatClient.Builder chatClientBuilder,
                                                ToolCallbackProvider tools,
                                                ConfigurableApplicationContext context) {
        return args -> {
            // 构建ChatClient并注入MCP工具
            var chatClient = chatClientBuilder
                    .defaultTools(tools)
                    .build();

            // 使用ChatClient与LLM交互
            String userInput = "北京的天气如何？";
            System.out.println("\n>>> QUESTION: " + userInput);
            System.out.println("\n>>> ASSISTANT: " + chatClient.prompt(userInput).call().content());

            context.close();
        };
    }
}

<dependency>
   <groupId>org.springframework.ai</groupId>
   <artifactId>spring-ai-mcp-server-spring-boot-starter</artifactId>
</dependency>

spring:
  main:
    web-application-type: none  # 必须禁用web应用类型
    banner-mode: off           # 禁用banner
  ai:
    mcp:
      server:
        stdio: true            # 启用stdio模式
        name: my-weather-server # 服务器名称
        version: 0.0.1         # 服务器版本

@Service
public class OpenMeteoService {

    private final WebClient webClient;

    public OpenMeteoService(WebClient.Builder webClientBuilder) {
        this.webClient = webClientBuilder
                .baseUrl("https://api.open-meteo.com/v1")
                .build();
    }

    @Tool(description = "根据经纬度获取天气预报")
    public String getWeatherForecastByLocation(
            @ToolParameter(description = "纬度，例如：39.9042") String latitude,
            @ToolParameter(description = "经度，例如：116.4074") String longitude) {

        try {
            String response = webClient.get()
                    .uri(uriBuilder -> uriBuilder
                            .path("/forecast")
                            .queryParam("latitude", latitude)
                            .queryParam("longitude", longitude)
                            .queryParam("current", "temperature_2m,wind_speed_10m")
                            .queryParam("timezone", "auto")
                            .build())
                    .retrieve()
                    .bodyToMono(String.class)
                    .block();

            // 解析响应并返回格式化的天气信息
            // 这里简化处理，实际应用中应该解析JSON
            return "当前位置（纬度：" + latitude + "，经度：" + longitude + "）的天气信息：\n" + response;
        } catch (Exception e) {
            return "获取天气信息失败：" + e.getMessage();
        }
    }

    @Tool(description = "根据经纬度获取空气质量信息")
    public String getAirQuality(
            @ToolParameter(description = "纬度，例如：39.9042") String latitude,
            @ToolParameter(description = "经度，例如：116.4074") String longitude) {

        // 模拟数据，实际应用中应调用真实API
        return "当前位置（纬度：" + latitude + "，经度：" + longitude + "）的空气质量：\n" +
                "- PM2.5: 15 μg/m³ (优)\n" +
                "- PM10: 28 μg/m³ (良)\n" +
                "- 空气质量指数(AQI): 42 (优)\n" +
                "- 主要污染物: 无";
    }
}

@SpringBootApplication
public class McpServerApplication {

    public static void main(String[] args) {
        SpringApplication.run(McpServerApplication.class, args);
    }

    @Bean
    public ToolCallbackProvider weatherTools(OpenMeteoService openMeteoService) {
        return MethodToolCallbackProvider.builder()
                .toolObjects(openMeteoService)
                .build();
    }
}

<dependency>
   <groupId>org.springframework.ai</groupId>
   <artifactId>spring-ai-mcp-server-webflux-spring-boot-starter</artifactId>
</dependency>

server:
  port: 8080  # 服务器端口配置

spring:
  ai:
    mcp:
      server:
        name: my-weather-server    # MCP服务器名称
        version: 0.0.1            # 服务器版本号

@Service
public class OpenMeteoService {

    private final WebClient webClient;

    public OpenMeteoService(WebClient.Builder webClientBuilder) {
        this.webClient = webClientBuilder
                .baseUrl("https://api.open-meteo.com/v1")
                .build();
    }

    @Tool(description = "根据经纬度获取天气预报")
    public String getWeatherForecastByLocation(
            @ToolParameter(description = "纬度，例如：39.9042") String latitude,
            @ToolParameter(description = "经度，例如：116.4074") String longitude) {

        try {
            String response = webClient.get()
                    .uri(uriBuilder -> uriBuilder
                            .path("/forecast")
                            .queryParam("latitude", latitude)
                            .queryParam("longitude", longitude)
                            .queryParam("current", "temperature_2m,wind_speed_10m")
                            .queryParam("timezone", "auto")
                            .build())
                    .retrieve()
                    .bodyToMono(String.class)
                    .block();

            // 解析响应并返回格式化的天气信息
            return "当前位置（纬度：" + latitude + "，经度：" + longitude + "）的天气信息：\n" + response;
        } catch (Exception e) {
            return "获取天气信息失败：" + e.getMessage();
        }
    }

    @Tool(description = "根据经纬度获取空气质量信息")
    public String getAirQuality(
            @ToolParameter(description = "纬度，例如：39.9042") String latitude,
            @ToolParameter(description = "经度，例如：116.4074") String longitude) {

        // 模拟数据，实际应用中应调用真实API
        return "当前位置（纬度：" + latitude + "，经度：" + longitude + "）的空气质量：\n" +
                "- PM2.5: 15 μg/m³ (优)\n" +
                "- PM10: 28 μg/m³ (良)\n" +
                "- 空气质量指数(AQI): 42 (优)\n" +
                "- 主要污染物: 无";
    }
}

@SpringBootApplication
public class McpServerApplication {

    public static void main(String[] args) {
        SpringApplication.run(McpServerApplication.class, args);
    }

    @Bean
    public ToolCallbackProvider weatherTools(OpenMeteoService openMeteoService) {
        return MethodToolCallbackProvider.builder()
                .toolObjects(openMeteoService)
                .build();
    }

    @Bean
    public WebClient.Builder webClientBuilder() {
        return WebClient.builder();
    }
}

// 客户端代码示例
var stdioParams = ServerParameters.builder("java")
        // 设置必要的系统属性
        .args("-Dspring.ai.mcp.server.stdio=true",
              "-Dspring.main.web-application-type=none",
              "-Dlogging.pattern.console=",
              "-jar",
              "target/mcp-stdio-server-example-0.0.1-SNAPSHOT.jar")
        .build();

// 创建基于stdio的传输层
var transport = new StdioClientTransport(stdioParams);
// 构建同步MCP客户端
var client = McpClient.sync(transport).build();

// 初始化客户端连接
client.initialize();

// 调用天气预报工具
CallToolResult weatherResult = client.callTool(
    new CallToolRequest("getWeatherForecastByLocation",
    Map.of("latitude", "39.9042", "longitude", "116.4074"))
);

// 打印结果
System.out.println(weatherResult.getContent());

// SSE客户端代码示例
var transport = new WebFluxSseClientTransport(
    // 配置WebClient基础URL
    WebClient.builder().baseUrl("http://localhost:8080")
);

// 构建同步MCP客户端
var client = McpClient.sync(transport).build();

// 初始化客户端连接
client.initialize();

// 调用天气预报工具
CallToolResult weatherResult = client.callTool(
    new CallToolRequest("getWeatherForecastByLocation",
    Map.of("latitude", "39.9042", "longitude", "116.4074"))
);

// 打印结果
System.out.println(weatherResult.getContent());