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Use this file to discover all available pages before exploring further.

The Java samples use Spring AI’s MCP Server Boot Starter and WebFlux for reactive SSE transport. Tools are registered declaratively with the @Tool annotation.

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Basic calculator server

Located at 03-GettingStarted/samples/java/calculator, this Spring Boot application exposes a full-featured calculator through MCP over SSE.
1

Clone and navigate

git clone https://github.com/microsoft/mcp-for-beginners.git
cd mcp-for-beginners/03-GettingStarted/samples/java/calculator
2

Build the project

./mvnw clean install -DskipTests
3

Run the server

java -jar target/calculator-server-0.0.1-SNAPSHOT.jar
The server starts on http://localhost:8080. The SSE endpoint is at /sse.

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Server code

package com.microsoft.mcp.sample.server;

import org.springframework.ai.tool.ToolCallbackProvider;
import org.springframework.ai.tool.method.MethodToolCallbackProvider;
import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;
import org.springframework.context.annotation.Bean;

@SpringBootApplication
public class McpServerApplication {

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

    @Bean
    public ToolCallbackProvider calculatorTools(CalculatorService calculator) {
        return MethodToolCallbackProvider.builder().toolObjects(calculator).build();
    }
}

​
Client code (MCP SDK)

SDKClient.java
import io.modelcontextprotocol.client.McpClient;
import io.modelcontextprotocol.client.transport.WebFluxSseClientTransport;
import io.modelcontextprotocol.spec.McpSchema.CallToolRequest;
import org.springframework.web.reactive.function.client.WebClient;

public class SDKClient {
    public static void main(String[] args) {
        var transport = new WebFluxSseClientTransport(
            WebClient.builder().baseUrl("http://localhost:8080")
        );
        var client = McpClient.sync(transport).build();
        client.initialize();

        // List available tools
        System.out.println(client.listTools());

        // Call the add tool
        var result = client.callTool(
            new CallToolRequest("add", Map.of("a", 5.0, "b", 3.0))
        );
        System.out.println("5 + 3 = " + result);

        // Call squareRoot
        var sqrt = client.callTool(
            new CallToolRequest("squareRoot", Map.of("number", 16.0))
        );
        System.out.println("√16 = " + sqrt);

        client.closeGracefully();
    }
}

​
LangChain4j client with GitHub models

The sample also includes a LangChain4jClient that connects an AI model to the calculator through MCP:
LangChain4jClient.java (excerpt)
ChatLanguageModel model = GitHubChatModel.builder()
    .apiKey(System.getenv("GITHUB_TOKEN"))
    .timeout(Duration.ofSeconds(60))
    .modelName("phi-4")
    .logRequests(true)
    .logResponses(true)
    .build();
Set your token before running:
export GITHUB_TOKEN=your-github-personal-access-token

​
Test with MCP Inspector

1

Start the Inspector

npx @modelcontextprotocol/inspector
2

Connect via SSE

  • Transport type: SSE
  • URL: http://localhost:8080/sse
  • Click Connect, then List Tools

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Run in Docker

docker build -t calculator-mcp-service .
docker run -p 8080:8080 calculator-mcp-service
The Dockerfile uses a multi-stage build with Maven 3.9.9 and Eclipse Temurin 24 JDK.

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Key Maven dependencies

pom.xml (excerpt)
<!-- MCP Server over SSE -->
<dependency>
    <groupId>org.springframework.ai</groupId>
    <artifactId>spring-ai-starter-mcp-server-webflux</artifactId>
</dependency>

<!-- LangChain4j MCP integration -->
<dependency>
    <groupId>dev.langchain4j</groupId>
    <artifactId>langchain4j-mcp</artifactId>
    <version>${langchain4j.version}</version>
</dependency>

<!-- GitHub model support -->
<dependency>
    <groupId>dev.langchain4j</groupId>
    <artifactId>langchain4j-github</artifactId>
    <version>${langchain4j.version}</version>
</dependency>

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