mcpbeat

MCP Server

rrezartprebreza/spring-boot-mcp-server

> Use when building MCP (Model Context Protocol) servers in Java/Spring Boot. Covers tool registration, resource exposure, prompt templates, and production deployment using the official MCP Java SDK. Use when user mentions MCP, AI agent integration, or tool calling.

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Install

one command, takes just this skill from the repository
npx skills add https://github.com/rrezartprebreza/spring-boot-skills --skill mcp-server

The instruction itself

10 sections, as written by the author

MCP Server — Java SDK

Official Java SDK: https://github.com/modelcontextprotocol/java-sdk

Maintained by Anthropic in collaboration with Spring AI.

Dependency

The standalone SDK reached 1.0.0 GA (io.modelcontextprotocol.sdk:mcp). Most Spring Boot

apps should use the Spring AI MCP starter instead — it auto-configures the server, transport,

and annotation-based tool scanning. In Spring AI 2.0, use spring-ai-starter-mcp-server-*

with spring.ai.mcp.server.protocol=STREAMABLE for remote HTTP.

<!-- Recommended for Spring Boot: pick ONE transport starter -->
<!-- stdio (Claude Desktop / Claude Code launching the jar locally) -->
<dependency>
    <groupId>org.springframework.ai</groupId>
    <artifactId>spring-ai-starter-mcp-server</artifactId>
</dependency>
<!-- OR remote HTTP (SSE + Streamable-HTTP) over Spring MVC -->
<dependency>
    <groupId>org.springframework.ai</groupId>
    <artifactId>spring-ai-starter-mcp-server-webmvc</artifactId>
</dependency>
<!-- OR reactive: spring-ai-starter-mcp-server-webflux -->
<!-- Or drive the raw SDK directly (no Spring AI), now at 1.0.0 GA -->
<dependency>
    <groupId>io.modelcontextprotocol.sdk</groupId>
    <artifactId>mcp</artifactId>
    <version>1.0.0</version>
</dependency>

> The old spring-ai-mcp-server-spring-boot-starter name is dead. GA is spring-ai-starter-mcp-server

> (stdio), -webmvc (servlet SSE / Streamable-HTTP), and -webflux (reactive).

Minimal MCP Server (stdio transport)

@SpringBootApplication
public class OrderMcpServer {
    public static void main(String[] args) {
        var transport = new StdioServerTransportProvider();

        var server = McpServer.sync(transport)
            .serverInfo("order-service-mcp", "1.0.0")
            .capabilities(ServerCapabilities.builder().tools(true).resources(true).build())
            .tools(getOrderTool(), listOrdersTool())
            .build();

        Runtime.getRuntime().addShutdownHook(new Thread(server::close));
    }
}

Defining Tools

// Tool with typed input/output
private static McpServerFeatures.SyncToolSpecification getOrderTool() {
    var schema = """
        {
          "type": "object",
          "properties": {
            "orderId": { "type": "string", "description": "UUID of the order" }
          },
          "required": ["orderId"]
        }
        """;

    return McpServerFeatures.SyncToolSpecification.builder()
        .tool(Tool.builder()
            .name("get_order")
            .description("Get a single order by ID including all line items and status history")
            .inputSchema(schema)
            .build())
        .callHandler((exchange, args) -> {
            String orderId = (String) args.get("orderId");
            try {
                Order order = orderService.findById(UUID.fromString(orderId));
                return new CallToolResult(List.of(
                    new TextContent(objectMapper.writeValueAsString(order))
                ), false);
            } catch (EntityNotFoundException e) {
                return new CallToolResult(List.of(
                    new TextContent("Order not found: " + orderId)
                ), true); // isError = true
            }
        })
        .build();
}

Spring AI 2.0 provides native MCP annotations. Use @McpTool for MCP server tools; @Tool is a

different Spring AI model tool-calling API and should only be used when intentionally registering

ToolCallback objects with the MCP tool-callback converter.

@Component
public class OrderMcpTools {

    private final OrderService orderService;

    public OrderMcpTools(OrderService orderService) {
        this.orderService = orderService;
    }

    @McpTool(
        name = "get_order",
        description = "Get an order by ID with line items and status history",
        generateOutputSchema = true)
    public OrderResponse getOrder(
            @McpToolParam(description = "UUID of the order", required = true) String orderId) {
        return OrderResponse.from(orderService.findById(UUID.fromString(orderId)));
    }

    @McpTool(
        name = "list_orders",
        description = "List orders for a customer, optionally filtered by status",
        generateOutputSchema = true)
    public List<OrderResponse> listOrders(
            @McpToolParam(description = "Customer email address", required = true) String email,
            @McpToolParam(description = "PENDING, PROCESSING, SHIPPED, or DELIVERED", required = false)
            String status) {
        List<Order> orders = status != null
            ? orderService.findByEmailAndStatus(email, OrderStatus.valueOf(status))
            : orderService.findByEmail(email);
        return orders.stream().map(OrderResponse::from).toList();
    }
}

With the Spring AI MCP starter, annotated @Component methods are discovered automatically. Do not

also create a MethodToolCallbackProvider for the same methods unless you intentionally choose the

alternative Spring AI tool-callback integration.

application.yml for MCP Server

spring:
  ai:
    mcp:
      server:
        name: order-service-mcp
        version: 1.0.0
        type: SYNC          # SYNC (blocking) or ASYNC (reactive / WebFlux)
        # --- stdio: needs spring-ai-starter-mcp-server + banner/console logging OFF ---
        stdio: true         # framing is over stdin/stdout — nothing else may write there
        # --- remote: needs the -webmvc or -webflux starter instead ---
        # protocol: STREAMABLE   # SSE | STREAMABLE | STATELESS (Streamable-HTTP preferred)

> stdio servers must keep stdout clean. Any log line, banner, or System.out.println corrupts

> the JSON-RPC framing and the client silently drops the connection. For stdio, set

> spring.main.banner-mode=off and route logging to a file or stderr.

Exposing Resources

@Bean
public List<McpServerFeatures.SyncResourceSpecification> mcpResources(OrderRepository repo) {
    return List.of(
        McpServerFeatures.SyncResourceSpecification.builder()
            .resource(Resource.builder()
                .uri("orders://recent")
                .name("Recent Orders")
                .description("Last 50 orders across all customers")
                .mimeType("application/json")
                .build())
            .readHandler((exchange, request) -> {
                List<Order> recent = repo.findTop50ByOrderByCreatedAtDesc();
                return new ReadResourceResult(List.of(
                    new TextResourceContents(request.uri(),
                        objectMapper.writeValueAsString(recent), "application/json")
                ));
            })
            .build()
    );
}

claude_desktop_config.json / .mcp.json

{
  "mcpServers": {
    "order-service": {
      "command": "java",
      "args": ["-jar", "/path/to/order-mcp-server.jar"],
      "env": {
        "SPRING_DATASOURCE_URL": "jdbc:postgresql://localhost:5432/orders"
      }
    }
  }
}

Error Handling Pattern

// Always return structured errors — never throw from tool handlers
private CallToolResult safeExecute(Supplier<Object> action) {
    try {
        return new CallToolResult(
            List.of(new TextContent(objectMapper.writeValueAsString(action.get()))),
            false
        );
    } catch (EntityNotFoundException e) {
        return errorResult("NOT_FOUND", e.getMessage());
    } catch (Exception e) {
        log.error("Tool execution failed", e);
        return errorResult("INTERNAL_ERROR", "Unexpected error occurred");
    }
}

private CallToolResult errorResult(String code, String message) {
    return new CallToolResult(
        List.of(new TextContent(String.format("{\"error\":\"%s\",\"message\":\"%s\"}", code, message))),
        true // isError flag — agent knows this is an error
    );
}

Gotchas

  • Agent generates Python MCP code — always use the Java SDK
  • Agent uses the dead spring-ai-mcp-server-spring-boot-starter name — Spring AI 2.0 uses spring-ai-starter-mcp-server[-webmvc|-webflux]
  • Agent uses @Tool when it needs native MCP server annotations — use @McpTool and @McpToolParam; @Tool belongs to Spring AI model tool calling
  • Agent enables remote HTTP with spring.ai.mcp.server.transport — use spring.ai.mcp.server.protocol=STREAMABLE / STATELESS
  • Agent pins SDK 0.9.0 — the standalone SDK is 1.0.0 GA (or just use the Spring AI starter)
  • Agent logs to stdout on a stdio server — corrupts JSON-RPC framing; banner off, logs to file/stderr
  • Agent forgets isError = true in error results — agent can't distinguish errors from data
  • Agent uses FetchType.EAGER inside tool handlers — triggers N+1, use projections
  • Agent exposes entities directly — serialize to DTOs before returning
  • Agent ignores shutdown hooks — always close the server on JVM shutdown
  • Agent writes vague tool descriptions — the description IS the prompt the model reads; be specific about when to call it and what it returns
  • stdio for local tools (Claude Code, Claude Desktop); -webmvc/-webflux + Streamable-HTTP for remote

How to use it

Copy the folder

Take rrezartprebreza/spring-boot-mcp-server from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.