spring-ai-mcp-server-patterns

name	spring-ai-mcp-server-patterns
description	Provides Model Context Protocol (MCP) server implementation patterns with Spring AI. Use when building MCP servers to extend AI capabilities with custom tools, resources, and prompt templates using Spring's official AI framework.
allowed-tools	Read, Write, Edit, Bash, Glob, Grep

Spring AI MCP Server Implementation Patterns

Implement Model Context Protocol (MCP) servers with Spring AI to extend AI capabilities with standardized tools, resources, and prompt templates using Spring's native AI abstractions.

Overview

The Model Context Protocol (MCP) is a standardized protocol for connecting AI applications to external data sources and tools. Spring AI provides native support for building MCP servers that expose Spring components as callable tools, resources, and prompt templates for AI models.

This skill covers the implementation patterns for creating production-ready MCP servers using Spring AI, including:

• Tools: Exposing Spring methods as AI-callable functions using @Tool annotation
• Resources: Data sources accessible through MCP endpoints
• Prompts: Reusable prompt templates with @PromptTemplate annotation
• Transport: Communication channels (stdio, HTTP, SSE)
• Security: Authentication, authorization, and input validation
• Testing: Unit and integration testing strategies

When to Use

Use this skill when building:

• AI applications requiring external tool integration with Spring AI
• Enterprise MCP servers with Spring ecosystem integration
• Function calling servers with Spring AI's declarative patterns
• Prompt template servers for standardized AI interactions
• Spring Boot applications with native MCP integration
• Production-ready MCP servers with Spring Security and monitoring
• Microservices that expose AI capabilities via MCP protocol
• Hybrid systems using both Spring AI and traditional Spring components

Instructions

Follow these steps to implement an MCP server with Spring AI:

1. Project Setup

1. Add Spring AI MCP dependencies to your pom.xml or build.gradle
2. Configure the AI model (OpenAI, Anthropic, etc.) in application.properties
3. Enable MCP server with @EnableMcpServer annotation

2. Define Tools

1. Create a Spring component class (@Component)
2. Annotate methods with @Tool(description = "...")
3. Use @ToolParam to document parameters for AI understanding
4. Implement business logic with proper error handling

3. Create Prompt Templates

1. Create prompt template components
2. Use @PromptTemplate for reusable prompts
3. Define parameters with @PromptParam
4. Return Prompt objects with system and user messages

4. Configure Transport

1. Choose transport type: stdio, http, or sse
2. Configure transport properties in application.yml
3. Set up CORS if using HTTP/SSE

5. Add Security

1. Implement Spring Security configuration
2. Create tool filters for role-based access control
3. Add input validation to prevent injection attacks
4. Implement audit logging for sensitive operations

6. Testing

1. Write unit tests for individual tools
2. Create integration tests for MCP endpoints
3. Test security configurations
4. Use Testcontainers for database-dependent tools

7. Deployment

1. Configure actuator endpoints for health checks
2. Set up metrics and monitoring
3. Implement rate limiting for production
4. Configure caching for frequently used operations

Quick Start

Basic MCP Server with Spring AI

Create a simple MCP server with function calling:

@SpringBootApplication
@EnableMcpServer
public class WeatherMcpApplication {

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

@Component
public class WeatherTools {

    @Tool(description = "Get current weather for a city")
    public WeatherData getWeather(@ToolParam("City name") String city) {
        // Implementation
        return new WeatherData(city, "Sunny", 22.5);
    }
}

Function Calling Setup

Configure function calling in application.properties:

spring.ai.openai.api-key=${OPENAI_API_KEY}
spring.ai.mcp.enabled=true
spring.ai.mcp.transport=stdio

Build Configuration

Add Spring AI MCP dependencies to your project:

Maven:

<dependency>
    <groupId>org.springframework.ai</groupId>
    <artifactId>spring-ai-mcp-server</artifactId>
    <version>1.0.0</version>
</dependency>
<dependency>
    <groupId>org.springframework.ai</groupId>
    <artifactId>spring-ai-starter-model-openai</artifactId>
    <version>1.0.0</version>
</dependency>

Gradle:

dependencies {
    implementation 'org.springframework.ai:spring-ai-mcp-server:1.0.0'
    implementation 'org.springframework.ai:spring-ai-starter-model-openai:1.0.0'
}

Or use Spring Boot starter:

<dependency>
    <groupId>org.springframework.ai</groupId>
    <artifactId>spring-ai-mcp-starter</artifactId>
    <version>1.0.0</version>
</dependency>

Core Concepts

MCP Architecture with Spring AI

MCP standardizes AI application connections with Spring AI abstractions:

• Tools: Executable functions using @Tool annotation
• Resources: Data sources accessible via Spring components
• Prompts: Template-based interactions with @PromptTemplate
• Transport: Spring-managed communication channels

AI Application ←→ MCP Client ←→ Spring AI ←→ MCP Server ←→ Spring Services

Key Spring AI Components

• @Tool: Declares methods as callable functions for AI models
• @ToolParam: Documents parameter purposes for AI understanding
• @PromptTemplate: Defines reusable prompt patterns
• @Model: Specifies AI model configurations
• FunctionCallback: Low-level function calling integration

Implementation Patterns

Tool Creation Pattern

Create tools with Spring AI's declarative approach:

@Component
public class DatabaseTools {

    private final JdbcTemplate jdbcTemplate;

    public DatabaseTools(JdbcTemplate jdbcTemplate) {
        this.jdbcTemplate = jdbcTemplate;
    }

    @Tool(description = "Execute a safe read-only SQL query")
    public List<Map<String, Object>> executeQuery(
            @ToolParam("SQL SELECT query") String query,
            @ToolParam(value = "Query parameters", required = false)
            Map<String, Object> params) {

        // Validate query is read-only
        if (!query.trim().toUpperCase().startsWith("SELECT")) {
            throw new IllegalArgumentException("Only SELECT queries are allowed");
        }

        return jdbcTemplate.queryForList(query, params);
    }

    @Tool(description = "Get table schema information")
    public TableSchema getTableSchema(
            @ToolParam("Table name") String tableName) {

        String sql = "SELECT column_name, data_type " +
                     "FROM information_schema.columns " +
                     "WHERE table_name = ?";

        List<Map<String, Object>> columns = jdbcTemplate.queryForList(sql, tableName);
        return new TableSchema(tableName, columns);
    }
}

record TableSchema(String tableName, List<Map<String, Object>> columns) {}

Advanced Tool Pattern with Validation

@Component
public class ApiTools {

    private final WebClient webClient;

    public ApiTools(WebClient.Builder webClientBuilder) {
        this.webClient = webClientBuilder.build();
    }

    @Tool(description = "Make HTTP GET request to an API")
    public ApiResponse callApi(
            @ToolParam("API URL") String url,
            @ToolParam(value = "Headers as JSON string", required = false)
            String headersJson) {

        // Validate URL
        try {
            new URL(url);
        } catch (MalformedURLException e) {
            throw new IllegalArgumentException("Invalid URL format");
        }

        // Parse headers if provided
        HttpHeaders headers = new HttpHeaders();
        if (headersJson != null && !headersJson.isBlank()) {
            try {
                Map<String, String> headersMap = new ObjectMapper()
                    .readValue(headersJson, Map.class);
                headersMap.forEach(headers::add);
            } catch (JsonProcessingException e) {
                throw new IllegalArgumentException("Invalid headers JSON");
            }
        }

        return webClient.get()
                .uri(url)
                .headers(h -> h.addAll(headers))
                .retrieve()
                .bodyToMono(ApiResponse.class)
                .block();
    }
}

record ApiResponse(int status, Map<String, Object> body, HttpHeaders headers) {}

Prompt Template Pattern

Create reusable prompt templates with Spring AI:

@Component
public class CodeReviewPrompts {

    @PromptTemplate(
        name = "java-code-review",
        description = "Review Java code for best practices and issues"
    )
    public Prompt createJavaCodeReviewPrompt(
            @PromptParam("code") String code,
            @PromptParam(value = "focusAreas", required = false)
            List<String> focusAreas) {

        String focus = focusAreas != null ?
            String.join(", ", focusAreas) :
            "general best practices";

        return Prompt.builder()
                .system("You are an expert Java code reviewer with 20 years of experience.")
                .user("""
                    Review the following Java code for {focus}:

                    ```java
                    {code}
                    ```

                    Provide feedback in the following format:
                    1. Critical issues (must fix)
                    2. Warnings (should fix)
                    3. Suggestions (consider improving)
                    4. Positive aspects

                    Be specific and provide code examples where relevant.
                    """.replace("{code}", code).replace("{focus}", focus))
                .build();
    }

    @PromptTemplate(
        name = "generate-unit-tests",
        description = "Generate comprehensive unit tests for Java code"
    )
    public Prompt createTestGenerationPrompt(
            @PromptParam("code") String code,
            @PromptParam("className") String className,
            @PromptParam(value = "testingFramework", required = false)
            String framework) {

        String testFramework = framework != null ? framework : "JUnit 5";

        return Prompt.builder()
                .system("You are an expert in test-driven development.")
                .user("""
                    Generate comprehensive unit tests for the following Java class using {testFramework}:

                    ```java
                    {code}
                    ```

                    Class: {className}

                    Requirements:
                    1. Test all public methods
                    2. Include edge cases and boundary conditions
                    3. Use appropriate assertions
                    4. Follow AAA pattern (Arrange, Act, Assert)
                    5. Include test method naming best practices
                    6. Mock external dependencies
                    """.replace("{code}", code)
                      .replace("{className}", className)
                      .replace("{testFramework}", testFramework))
                .build();
    }
}

Function Callback Pattern

Low-level function calling integration:

@Configuration
public class FunctionConfig {

    @Bean
    public FunctionCallback weatherFunction() {
        return FunctionCallback.builder()
                .function("getCurrentWeather", new WeatherService())
                .description("Get the current weather for a location")
                .inputType(WeatherRequest.class)
                .build();
    }

    @Bean
    public FunctionCallback calculatorFunction() {
        return FunctionCallbackWrapper.builder(new Calculator())
                .withName("calculate")
                .withDescription("Perform mathematical calculations")
                .build();
    }
}

class WeatherService implements Function<WeatherRequest, WeatherResponse> {
    @Override
    public WeatherResponse apply(WeatherRequest request) {
        // Call weather API
        return new WeatherResponse(request.location(), 72, "Sunny");
    }
}

record WeatherRequest(String location) {}
record WeatherResponse(String location, double temperature, String condition) {}

class Calculator implements BiFunction<String, Map<String, Object>, String> {
    @Override
    public String apply(String functionName, Map<String, Object> args) {
        // Perform calculation based on args
        return "result";
    }
}

Spring Boot Integration

Auto-Configuration

Set up MCP server with Spring Boot auto-configuration:

@Configuration
@AutoConfigureAfter({WebMvcAutoConfiguration.class})
@ConditionalOnClass({McpServer.class, ChatModel.class})
@ConditionalOnProperty(name = "spring.ai.mcp.enabled", havingValue = "true", matchIfMissing = true)
public class McpAutoConfiguration {

    @Bean
    @ConditionalOnMissingBean
    public McpServerProperties mcpServerProperties() {
        return new McpServerProperties();
    }

    @Bean
    @ConditionalOnMissingBean
    public McpServer mcpServer(
            List<FunctionCallback> functionCallbacks,
            List<PromptTemplate> promptTemplates,
            McpServerProperties properties
    ) {
        McpServer.Builder builder = McpServer.builder()
                .serverInfo("spring-ai-mcp", "1.0.0")
                .transport(properties.getTransport().create());

        // Register function callbacks as tools
        functionCallbacks.forEach(callback ->
                builder.tool(Tool.fromFunctionCallback(callback))
        );

        // Register prompt templates
        promptTemplates.forEach(template ->
                builder.prompt(Prompt.fromTemplate(template))
        );

        return builder.build();
    }

    @Bean
    @ConditionalOnProperty(name = "spring.ai.mcp.actuator.enabled", havingValue = "true")
    public McpHealthIndicator mcpHealthIndicator(McpServer mcpServer) {
        return new McpHealthIndicator(mcpServer);
    }
}

@ConfigurationProperties(prefix = "spring.ai.mcp")
public class McpServerProperties {
    private boolean enabled = true;
    private TransportConfig transport = new TransportConfig();
    private ActuatorConfig actuator = new ActuatorConfig();

    // Getters and setters

    public static class TransportConfig {
        private TransportType type = TransportType.STDIO;
        private HttpConfig http = new HttpConfig();

        public Transport create() {
            return switch (type) {
                case STDIO -> new StdioTransport();
                case HTTP -> new HttpTransport(http.getPort());
                case SSE -> new SseTransport(http.getPort(), http.getPath());
            };
        }
    }

    public static class HttpConfig {
        private int port = 8080;
        private String path = "/mcp";
        // Getters and setters
    }

    public static class ActuatorConfig {
        private boolean enabled = true;
        // Getters and setters
    }

    public enum TransportType {
        STDIO, HTTP, SSE
    }
}

Application Properties

Configure MCP server in application.yml:

spring:
  ai:
    mcp:
      enabled: true
      transport:
        type: stdio  # Options: stdio, http, sse
        http:
          port: 8080
          path: /mcp
      actuator:
        enabled: true
      tools:
        package-scan: com.example.tools
      prompts:
        package-scan: com.example.prompts
      security:
        enabled: true
        allowed-tools:
          - getWeather
          - executeQuery
        admin-tools:
          - admin_*

Custom Server Configuration

For advanced configuration:

@Configuration
public class CustomMcpConfig {

    @Bean
    public McpServerCustomizer mcpServerCustomizer() {
        return server -> {
            server.addToolInterceptor((tool, args, chain) -> {
                log.info("Executing tool: {}", tool.name());
                long start = System.currentTimeMillis();
                Object result = chain.execute(tool, args);
                long duration = System.currentTimeMillis() - start;
                log.info("Tool {} executed in {}ms", tool.name(), duration);
                metrics.recordToolExecution(tool.name(), duration);
                return result;
            });
        };
    }

    @Bean
    public ToolFilter toolFilter(SecurityService securityService) {
        return (tool, context) -> {
            User user = securityService.getCurrentUser();
            if (tool.name().startsWith("admin_")) {
                return user.hasRole("ADMIN");
            }
            return securityService.isToolAllowed(user, tool.name());
        };
    }
}

@Service
public class SecurityService {
    public boolean isToolAllowed(User user, String toolName) {
        // Implement tool access control logic
        return true;
    }
}

Security & Best Practices

Tool Security

Implement secure tool execution with Spring Security:

@Component
public class SecureToolExecutor {

    private final McpServer mcpServer;
    private final SecurityContextHolder strategy;

    public SecureToolExecutor(McpServer mcpServer, SecurityContextHolder strategy) {
        this.mcpServer = mcpServer;
        this.strategy = strategy;
    }

    public ToolResult executeTool(String toolName, Map<String, Object> arguments) {
        Authentication auth = SecurityContextHolder.getContext().getAuthentication();

        if (!(auth instanceof UserAuthentication userAuth)) {
            throw new AccessDeniedException("User not authenticated");
        }

        // Check tool permissions
        if (!hasToolPermission(userAuth.getUser(), toolName)) {
            throw new AccessDeniedException("Tool not allowed: " + toolName);
        }

        // Validate arguments against injection patterns
        validateArguments(arguments);

        // Execute with audit logging
        logToolExecution(userAuth.getUser(), toolName, arguments);

        try {
            ToolResult result = mcpServer.executeTool(toolName, arguments);
            logToolSuccess(userAuth.getUser(), toolName);
            return result;
        } catch (Exception e) {
            logToolFailure(userAuth.getUser(), toolName, e);
            throw new ToolExecutionException("Tool execution failed", e);
        }
    }

    private boolean hasToolPermission(User user, String toolName) {
        // Implement permission logic based on user roles and tool sensitivity
        return user.getAuthorities().stream()
                .anyMatch(auth -> auth.getAuthority().equals("TOOL_" + toolName) ||
                                 auth.getAuthority().equals("ROLE_ADMIN"));
    }

    private void validateArguments(Map<String, Object> arguments) {
        // Implement argument validation to prevent injection attacks
        arguments.forEach((key, value) -> {
            if (value instanceof String str) {
                if (str.contains(";") || str.contains("--")) {
                    throw new IllegalArgumentException("Invalid characters in argument: " + key);
                }
            }
        });
    }

    private void logToolExecution(User user, String toolName, Map<String, Object> arguments) {
        // Implement audit logging
    }

    private void logToolSuccess(User user, String toolName) {
        // Log successful execution
    }

    private void logToolFailure(User user, String toolName, Exception e) {
        // Log failed execution
    }
}

class ToolExecutionException extends RuntimeException {
    public ToolExecutionException(String message, Throwable cause) {
        super(message, cause);
    }
}

Input Validation

Use Spring's validation framework:

@Component
public class ValidatedTools {

    @Tool(description = "Process user data with validation")
    @Validated
    public ProcessingResult processUserData(
            @ToolParam("User data to process") @Valid UserData data) {
        // Implementation
        return new ProcessingResult("success", data);
    }
}

record UserData(
    @NotBlank(message = "Name is required")
    @Size(max = 100, message = "Name must be 100 characters or less")
    String name,

    @NotNull(message = "Age is required")
    @Min(value = 18, message = "Must be 18 or older")
    @Max(value = 120, message = "Age must be realistic")
    Integer age,

    @NotBlank(message = "Email is required")
    @Email(message = "Invalid email format")
    String email
) {}

// Custom validator for sensitive operations
@Component
public class SensitiveOperationValidator {

    public void validateOperation(String operation, User user, Map<String, Object> params) {
        if (isSensitiveOperation(operation)) {
            requireAdditionalAuthentication(user);
            validateOperationLimits(user, operation);
            logSensitiveOperation(user, operation, params);
        }
    }

    private boolean isSensitiveOperation(String operation) {
        return operation.startsWith("delete") || operation.startsWith("update");
    }

    private void requireAdditionalAuthentication(User user) {
        // Implement MFA or re-authentication
    }

    private void validateOperationLimits(User user, String operation) {
        // Check rate limits and quotas
    }

    private void logSensitiveOperation(User user, String operation, Map<String, Object> params) {
        // Secure audit logging
    }
}

Error Handling

Implement comprehensive error handling:

@ControllerAdvice
public class McpExceptionHandler {

    @ExceptionHandler(ToolExecutionException.class)
    public ResponseEntity<ErrorResponse> handleToolExecutionException(
            ToolExecutionException ex, WebRequest request) {

        ErrorResponse error = ErrorResponse.builder()
                .timestamp(LocalDateTime.now())
                .status(HttpStatus.INTERNAL_SERVER_ERROR.value())
                .error("Tool Execution Failed")
                .message(ex.getMessage())
                .path(((ServletWebRequest) request).getRequest().getRequestURI())
                .build();

        log.error("Tool execution failed: {}", ex.getMessage(), ex);
        return new ResponseEntity<>(error, HttpStatus.INTERNAL_SERVER_ERROR);
    }

    @ExceptionHandler(AccessDeniedException.class)
    public ResponseEntity<ErrorResponse> handleAccessDenied(
            AccessDeniedException ex, WebRequest request) {

        ErrorResponse error = ErrorResponse.builder()
                .timestamp(LocalDateTime.now())
                .status(HttpStatus.FORBIDDEN.value())
                .error("Access Denied")
                .message("You do not have permission to execute this tool")
                .path(((ServletWebRequest) request).getRequest().getRequestURI())
                .build();

        log.warn("Access denied: {}", ex.getMessage());
        return new ResponseEntity<>(error, HttpStatus.FORBIDDEN);
    }

    @ExceptionHandler(IllegalArgumentException.class)
    public ResponseEntity<ErrorResponse> handleValidationError(
            IllegalArgumentException ex, WebRequest request) {

        ErrorResponse error = ErrorResponse.builder()
                .timestamp(LocalDateTime.now())
                .status(HttpStatus.BAD_REQUEST.value())
                .error("Validation Error")
                .message(ex.getMessage())
                .path(((ServletWebRequest) request).getRequest().getRequestURI())
                .build();

        return new ResponseEntity<>(error, HttpStatus.BAD_REQUEST);
    }

    @ExceptionHandler(Exception.class)
    public ResponseEntity<ErrorResponse> handleGenericException(
            Exception ex, WebRequest request) {

        ErrorResponse error = ErrorResponse.builder()
                .timestamp(LocalDateTime.now())
                .status(HttpStatus.INTERNAL_SERVER_ERROR.value())
                .error("Internal Server Error")
                .message("An unexpected error occurred")
                .path(((ServletWebRequest) request).getRequest().getRequestURI())
                .build();

        log.error("Unexpected error: {}", ex.getMessage(), ex);
        return new ResponseEntity<>(error, HttpStatus.INTERNAL_SERVER_ERROR);
    }

    @Data
    @Builder
    static class ErrorResponse {
        private LocalDateTime timestamp;
        private int status;
        private String error;
        private String message;
        private String path;
    }
}

Advanced Patterns

Dynamic Tool Registration

Register tools at runtime:

public class DynamicToolRegistry {

    private final McpServer mcpServer;
    private final Map<String, ToolRegistration> registeredTools = new ConcurrentHashMap<>();

    public DynamicToolRegistry(McpServer mcpServer) {
        this.mcpServer = mcpServer;
    }

    public void registerTool(ToolRegistration registration) {
        registeredTools.put(registration.getId(), registration);

        Tool tool = Tool.builder()
                .name(registration.getName())
                .description(registration.getDescription())
                .inputSchema(registration.getInputSchema())
                .function(args -> executeDynamicTool(registration.getId(), args))
                .build();

        mcpServer.addTool(tool);
        log.info("Registered dynamic tool: {}", registration.getName());
    }

    public void unregisterTool(String toolId) {
        ToolRegistration registration = registeredTools.remove(toolId);
        if (registration != null) {
            mcpServer.removeTool(registration.getName());
            log.info("Unregistered dynamic tool: {}", registration.getName());
        }
    }

    private Object executeDynamicTool(String toolId, Map<String, Object> args) {
        ToolRegistration registration = registeredTools.get(toolId);
        if (registration == null) {
            throw new IllegalStateException("Tool not found: " + toolId);
        }

        // Execute based on registration type
        return switch (registration.getType()) {
            case GROOVY_SCRIPT -> executeGroovyScript(registration, args);
            case SPRING_BEAN -> executeSpringBeanMethod(registration, args);
            case HTTP_ENDPOINT -> callHttpEndpoint(registration, args);
        };
    }

    private Object executeGroovyScript(ToolRegistration registration, Map<String, Object> args) {
        // Implement Groovy script execution
        return null;
    }

    private Object executeSpringBeanMethod(ToolRegistration registration, Map<String, Object> args) {
        // Implement Spring bean method invocation
        return null;
    }

    private Object callHttpEndpoint(ToolRegistration registration, Map<String, Object> args) {
        // Implement HTTP call
        return null;
    }
}

@Data
@Builder
class ToolRegistration {
    private String id;
    private String name;
    private String description;
    private Map<String, Object> inputSchema;
    private ToolType type;
    private String target; // script, bean name, or URL
    private Map<String, String> metadata;
}

enum ToolType {
    GROOVY_SCRIPT,
    SPRING_BEAN,
    HTTP_ENDPOINT
}

Multi-Model Support

Support multiple AI models:

@Configuration
public class MultiModelConfig {

    @Bean
    @Primary
    public ChatModel primaryChatModel(@Value("${spring.ai.primary.model}") String modelName) {
        return switch (modelName) {
            case "gpt-4" -> new OpenAiChatModel(OpenAiApi.builder()
                    .apiKey(System.getenv("OPENAI_API_KEY"))
                    .build());
            case "claude" -> new AnthropicChatModel(AnthropicApi.builder()
                    .apiKey(System.getenv("ANTHROPIC_API_KEY"))
                    .build());
            default -> throw new IllegalArgumentException("Unsupported model: " + modelName);
        };
    }

    @Bean
    public Map<String, ChatModel> allChatModels() {
        Map<String, ChatModel> models = new HashMap<>();

        models.put("gpt-4", new OpenAiChatModel(OpenAiApi.builder()
                .apiKey(System.getenv("OPENAI_API_KEY"))
                .build()));

        models.put("gpt-3.5", new OpenAiChatModel(OpenAiApi.builder()
                .apiKey(System.getenv("OPENAI_API_KEY"))
                .model("gpt-3.5-turbo")
                .build()));

        models.put("claude-opus", new AnthropicChatModel(AnthropicApi.builder()
                .apiKey(System.getenv("ANTHROPIC_API_KEY"))
                .model("claude-3-opus-20240229")
                .build()));

        return models;
    }

    @Bean
    public ModelSelector modelSelector(Map<String, ChatModel> models) {
        return new SpringAiModelSelector(models);
    }
}

@Component
public class SpringAiModelSelector implements ModelSelector {

    private final Map<String, ChatModel> models;

    public SpringAiModelSelector(Map<String, ChatModel> models) {
        this.models = models;
    }

    @Override
    public ChatModel selectModel(Prompt prompt, Map<String, Object> context) {
        // Select model based on prompt complexity, cost, latency requirements
        String modelName = determineBestModel(prompt, context);
        return models.get(modelName);
    }

    private String determineBestModel(Prompt prompt, Map<String, Object> context) {
        // Implement model selection logic
        // Consider: prompt length, complexity, cost constraints, latency requirements
        return "gpt-4";
    }
}

Caching and Performance

Implement caching for tools and prompts:

@Configuration
@EnableCaching
public class McpCacheConfig {

    @Bean
    public CacheManager cacheManager() {
        return new ConcurrentMapCacheManager(
            "tool-results",
            "prompt-templates",
            "function-callbacks"
        );
    }
}

@Component
public class CachedToolExecutor {

    private final McpServer mcpServer;

    public CachedToolExecutor(McpServer mcpServer) {
        this.mcpServer = mcpServer;
    }

    @Cacheable(
        value = "tool-results",
        key = "#toolName + '_' + #args.hashCode()",
        unless = "#result.isCacheable() == false"
    )
    public ToolResult executeTool(String toolName, Map<String, Object> args) {
        return mcpServer.executeTool(toolName, args);
    }

    @CacheEvict(value = "tool-results", allEntries = true)
    public void clearToolCache() {
        // Clear cache when tools are updated
    }

    @Cacheable(value = "prompt-templates", key = "#templateName")
    public PromptTemplate getPromptTemplate(String templateName) {
        return mcpServer.getPromptTemplate(templateName);
    }
}

Testing

Unit Testing Tools

@SpringBootTest
class DatabaseToolsTest {

    @Autowired
    private DatabaseTools databaseTools;

    @MockBean
    private JdbcTemplate jdbcTemplate;

    @Test
    void testExecuteQuery_Success() {
        // Given
        String query = "SELECT * FROM users WHERE id = ?";
        Map<String, Object> params = Map.of("id", 1);

        List<Map<String, Object>> expectedResults = List.of(
            Map.of("id", 1, "name", "John")
        );

        when(jdbcTemplate.queryForList(anyString(), anyMap()))
            .thenReturn(expectedResults);

        // When
        List<Map<String, Object>> results = databaseTools.executeQuery(query, params);

        // Then
        assertThat(results).isEqualTo(expectedResults);
        verify(jdbcTemplate).queryForList(query, params);
    }

    @Test
    void testExecuteQuery_InvalidQuery_ThrowsException() {
        // Given
        String query = "DROP TABLE users";

        // When & Then
        assertThatThrownBy(() -> databaseTools.executeQuery(query, null))
            .isInstanceOf(IllegalArgumentException.class)
            .hasMessage("Only SELECT queries are allowed");

        verifyNoInteractions(jdbcTemplate);
    }

    @Test
    void testGetTableSchema_Success() {
        // Given
        String tableName = "users";
        List<Map<String, Object>> columns = List.of(
            Map.of("column_name", "id", "data_type", "integer"),
            Map.of("column_name", "name", "data_type", "varchar")
        );

        when(jdbcTemplate.queryForList(anyString(), eq(tableName)))
            .thenReturn(columns);

        // When
        TableSchema schema = databaseTools.getTableSchema(tableName);

        // Then
        assertThat(schema.tableName()).isEqualTo(tableName);
        assertThat(schema.columns()).isEqualTo(columns);
    }
}

Integration Testing

@SpringBootTest
@AutoConfigureMockMvc
class McpServerIntegrationTest {

    @Autowired
    private MockMvc mockMvc;

    @Autowired
    private McpServer mcpServer;

    @MockBean
    private DatabaseTools databaseTools;

    @Test
    void testExecuteTool_Success() throws Exception {
        // Given
        String toolName = "executeQuery";
        Map<String, Object> args = Map.of(
            "query", "SELECT * FROM users",
            "params", Map.of()
        );

        List<Map<String, Object>> expectedResult = List.of(
            Map.of("id", 1, "name", "Test User")
        );

        when(databaseTools.executeQuery(anyString(), anyMap()))
            .thenReturn(expectedResult);

        // When & Then
        mockMvc.perform(post("/mcp/tools/executeQuery")
                .contentType(MediaType.APPLICATION_JSON)
                .content(new ObjectMapper().writeValueAsString(args)))
                .andExpect(status().isOk())
                .andExpect(jsonPath("$.result").isArray())
                .andExpect(jsonPath("$.result[0].id").value(1));
    }

    @Test
    void testListTools_Success() throws Exception {
        // When & Then
        mockMvc.perform(get("/mcp/tools"))
                .andExpect(status().isOk())
                .andExpect(jsonPath("$.tools").isArray());
    }

    @Test
    void testHealthEndpoint() throws Exception {
        // When & Then
        mockMvc.perform(get("/actuator/health/mcp"))
                .andExpect(status().isOk())
                .andExpect(jsonPath("$.status").value("UP"));
    }
}

Integration Testing with Testcontainers

@SpringBootTest
@Testcontainers
@AutoConfigureMockMvc
class McpServerIntegrationTest {

    @Container
    static PostgreSQLContainer<?> postgres = new PostgreSQLContainer<>("postgres:15")
            .withDatabaseName("testdb")
            .withUsername("test")
            .withPassword("test");

    @DynamicPropertySource
    static void properties(DynamicPropertyRegistry registry) {
        registry.add("spring.datasource.url", postgres::getJdbcUrl);
        registry.add("spring.datasource.username", postgres::getUsername);
        registry.add("spring.datasource.password", postgres::getPassword);
    }

    @Autowired
    private MockMvc mockMvc;

    @Test
    void testDatabaseToolWithRealDatabase() throws Exception {
        // Given
        String query = "SELECT current_database(), current_user";
        Map<String, Object> request = Map.of(
                "tool", "executeQuery",
                "arguments", Map.of("query", query)
        );

        // When & Then
        mockMvc.perform(post("/mcp/tools/executeQuery")
                .contentType(MediaType.APPLICATION_JSON)
                .content(new ObjectMapper().writeValueAsString(request)))
                .andExpect(status().isOk())
                .andExpect(jsonPath("$.success").value(true))
                .andExpect(jsonPath("$.data[0].current_database").value("testdb"))
                .andExpect(jsonPath("$.data[0].current_user").value("test"));
    }
}

Testing with @WebMvcTest (Slice Test)

@WebMvcTest(controllers = McpController.class)
class McpControllerSliceTest {

    @Autowired
    private MockMvc mockMvc;

    @MockBean
    private McpServer mcpServer;

    @MockBean
    private ToolRegistry toolRegistry;

    @Test
    void testListToolsEndpoint() throws Exception {
        // Given
        Tool tool1 = Tool.builder().name("tool1").description("Tool 1").build();
        Tool tool2 = Tool.builder().name("tool2").description("Tool 2").build();

        when(toolRegistry.listTools()).thenReturn(List.of(tool1, tool2));

        // When & Then
        mockMvc.perform(get("/mcp/tools"))
                .andExpect(status().isOk())
                .andExpect(jsonPath("$.tools").isArray())
                .andExpect(jsonPath("$.tools.length()").value(2))
                .andExpect(jsonPath("$.tools[0].name").value("tool1"));
    }
}

Testing Tool Validation

@ExtendWith(MockitoExtension.class)
class ToolValidationTest {

    private ToolValidator validator;

    @BeforeEach
    void setUp() {
        McpServerProperties properties = new McpServerProperties();
        properties.getTools().getValidation().setMaxArgumentsSize(1000);
        validator = new DefaultToolValidator(properties);
    }

    @Test
    void testValidArguments() {
        // Given
        Tool tool = Tool.builder()
                .name("testTool")
                .method(getTestMethod())
                .build();
        Map<String, Object> args = Map.of("param1", "value1", "param2", 123);

        // When & Then
        assertDoesNotThrow(() -> validator.validateArguments(tool, args));
    }

    @Test
    void testArgumentsTooLarge() {
        // Given
        Tool tool = Tool.builder().name("testTool").build();
        Map<String, Object> args = Map.of("largeParam", "x".repeat(2000));

        // When & Then
        ValidationException exception = assertThrows(
                ValidationException.class,
                () -> validator.validateArguments(tool, args)
        );
        assertThat(exception.getMessage()).contains("Arguments too large");
    }
}

Testing Security Integration

@SpringBootTest
@AutoConfigureMockMvc
@WithMockUser(roles = {"USER"})
class McpSecurityTest {

    @Autowired
    private MockMvc mockMvc;

    @Test
    void testUserCanAccessRegularTools() throws Exception {
        mockMvc.perform(get("/mcp/tools/getWeather"))
                .andExpect(status().isOk());
    }

    @Test
    @WithMockUser(roles = {"USER"})
    void testUserCannotAccessAdminTools() throws Exception {
        mockMvc.perform(get("/mcp/tools/admin/deleteData"))
                .andExpect(status().isForbidden());
    }

    @Test
    @WithMockUser(roles = {"ADMIN"})
    void testAdminCanAccessAllTools() throws Exception {
        mockMvc.perform(get("/mcp/tools/admin/deleteData"))
                .andExpect(status().isOk());
    }
}

Configuration Testing

@SpringBootTest
@EnableConfigurationProperties(McpServerProperties.class)
class McpPropertiesTest {

    @Autowired
    private McpServerProperties properties;

    @Test
    void testDefaultValues() {
        assertThat(properties.getServer().getName()).isEqualTo("spring-ai-mcp-server");
        assertThat(properties.getTransport().getType()).isEqualTo(TransportType.STDIO);
        assertThat(properties.getSecurity().isEnabled()).isFalse();
    }
}

application.properties

# Spring AI Configuration
spring.ai.openai.api-key=${OPENAI_API_KEY}
spring.ai.openai.chat.options.model=gpt-4o-mini
spring.ai.openai.chat.options.temperature=0.7

# MCP Server Configuration
spring.ai.mcp.enabled=true
spring.ai.mcp.server.name=spring-ai-mcp-server
spring.ai.mcp.server.version=1.0.0
spring.ai.mcp.transport.type=stdio

# HTTP Transport (if enabled)
spring.ai.mcp.transport.http.port=8080
spring.ai.mcp.transport.http.path=/mcp
spring.ai.mcp.transport.http.cors.enabled=true
spring.ai.mcp.transport.http.cors.allowed-origins=*

# Security Configuration
spring.ai.mcp.security.enabled=true
spring.ai.mcp.security.authorization.mode=role-based
spring.ai.mcp.security.authorization.default-deny=true
spring.ai.mcp.security.audit.enabled=true

# Tool Configuration
spring.ai.mcp.tools.package-scan=com.example.mcp.tools
spring.ai.mcp.tools.validation.enabled=true
spring.ai.mcp.tools.validation.max-execution-time=30s
spring.ai.mcp.tools.caching.enabled=true
spring.ai.mcp.tools.caching.ttl=5m

# Prompt Configuration
spring.ai.mcp.prompts.package-scan=com.example.mcp.prompts
spring.ai.mcp.prompts.caching.enabled=true
spring.ai.mcp.prompts.caching.ttl=1h

# Actuator and Monitoring
spring.ai.mcp.actuator.enabled=true
spring.ai.mcp.metrics.enabled=true
spring.ai.mcp.metrics.export.prometheus.enabled=true
spring.ai.mcp.logging.enabled=true
spring.ai.mcp.logging.level=DEBUG

# Performance Tuning
spring.ai.mcp.thread-pool.core-size=10
spring.ai.mcp.thread-pool.max-size=50
spring.ai.mcp.thread-pool.queue-capacity=100
spring.ai.mcp.rate-limiter.enabled=true
spring.ai.mcp.rate-limiter.requests-per-minute=100

Best Practices

Tool Design

1. Use Declarative Annotations: Prefer @Tool and @PromptTemplate over manual registration for cleaner, more maintainable code.

2. Keep Tools Focused: Each tool should do one thing well. Avoid creating monolithic tools that handle multiple unrelated operations.

3. Use Descriptive Names: Tool names should clearly indicate what they do. Use verbs like get, create, update, delete, search for actions.

4. Document Parameters: Use @ToolParam with clear descriptions so AI models understand when and how to use each parameter.

5. Return Structured Data: Use records or DTOs for return values instead of raw strings or maps to provide schema information to AI models.

Security Practices

6. Implement Input Validation: Always validate user inputs to prevent injection attacks. Never trust AI-generated parameters without validation.

7. Use Authorization: Implement role-based access control for sensitive operations. Use Spring Security annotations like @PreAuthorize.

8. Sanitize Error Messages: Never expose sensitive information in error messages or tool descriptions.

9. Audit Sensitive Operations: Log all executions of tools that modify data or access sensitive resources.

10. Rate Limiting: Implement rate limiting for expensive operations to prevent abuse and ensure fair usage.

Performance Optimization

11. Use Caching: Cache results of expensive operations using Spring Cache with @Cacheable. Set appropriate TTL values.

12. Implement Timeouts: Always set timeouts for external API calls to prevent hanging requests.

13. Use Async Processing: For long-running operations, consider using @Async to return immediately and provide status updates.

14. Connection Pooling: Configure proper connection pools for database and HTTP clients.

15. Monitor Performance: Track tool execution times and success rates using Micrometer metrics.

Error Handling

16. Handle Errors Gracefully: Implement proper exception handling with user-friendly error messages.

17. Use Specific Exceptions: Create custom exceptions for different error scenarios to enable proper error handling.

18. Implement Fallback: Provide fallback values or retry logic for transient failures.

19. Log Context: Include relevant context (user, tool name, parameters) in error logs for debugging.

Testing

20. Write Unit Tests: Test each tool independently with mocked dependencies.

21. Write Integration Tests: Test the entire MCP server flow including transport and serialization.

22. Test Security: Verify that authorization rules are properly enforced.

23. Use Testcontainers: For database-dependent tools, use Testcontainers for realistic testing.

24. Test Edge Cases: Test with invalid inputs, null values, and boundary conditions.

Documentation

25. Document Tool Purpose: Clearly describe what each tool does and when to use it.

26. Provide Examples: Include usage examples in the tool description or separate documentation.

27. Version Your API: Maintain backward compatibility when updating tools. Use semantic versioning.

28. Document Return Types: Clearly describe the structure of return values.

Configuration

29. Externalize Configuration: Use application.yml for configurable values like URLs, timeouts, and credentials.

30. Use Profiles: Define different configurations for dev, test, and production environments.

31. Validate Configuration: Use @ConfigurationProperties with validation for type-safe configuration.

Spring-Specific Best Practices

32. Leverage Dependency Injection: Use constructor injection for dependencies to improve testability.

33. Use Qualifiers: When multiple beans of the same type exist, use @Qualifier to disambiguate.

34. Implement Health Checks: Provide health indicators to monitor MCP server status.

35. Use Profiles: Different configurations for development and production environments.

AI-Specific Considerations

36. Design for Idempotency: Tools should be idempotent when possible as AI models may retry failed calls.

37. Be Conservative with Data Modifying Tools: AI models may call modifying tools unexpectedly - consider adding confirmation steps.

38. Provide Context: Include relevant context in responses to help AI models understand results.

39. Handle Large Responses: For tools that return large data, consider pagination or summary options.

Migration from LangChain4j

If migrating from LangChain4j MCP to Spring AI MCP:

Key Differences

• Annotations: Spring AI uses @Tool instead of LangChain4j's @ToolMethod
• Configuration: Spring AI emphasizes auto-configuration and properties
• Integration: Deeper integration with Spring ecosystem (Security, Data, WebFlux)
• Function Calling: Spring AI uses FunctionCallback for low-level control

Migration Steps

1. Replace LangChain4j @ToolMethod with Spring AI @Tool
2. Update configuration from application.properties to Spring AI properties
3. Migrate tool providers to Spring components with @Component
4. Update prompt templates to use Spring AI's prompt abstractions
5. Replace LangChain4j-specific types with Spring AI equivalents

Example Migration

// Before: LangChain4j
@ToolMethod("Get weather information")
public String getWeather(@P("city name") String city) {
    return weatherService.getWeather(city);
}

// After: Spring AI
@Component
public class WeatherTools {
    @Tool(description = "Get weather information")
    public String getWeather(@ToolParam("City name") String city) {
        return weatherService.getWeather(city);
    }
}

Examples

Example 1: Complete Weather MCP Server

A complete, production-ready weather MCP server:

// Application.java
@SpringBootApplication
@EnableMcpServer
public class WeatherMcpServerApplication {
    public static void main(String[] args) {
        SpringApplication.run(WeatherMcpServerApplication.class, args);
    }
}

// WeatherTools.java
@Component
@Slf4j
public class WeatherTools {

    private final WeatherService weatherService;
    private final MeterRegistry meterRegistry;

    public WeatherTools(WeatherService weatherService, MeterRegistry meterRegistry) {
        this.weatherService = weatherService;
        this.meterRegistry = meterRegistry;
    }

    @Tool(description = "Get current weather conditions for a city")
    public WeatherResponse getCurrentWeather(
            @ToolParam("City name (e.g., 'New York, NY')") String city) {

        Timer.Sample sample = Timer.start(meterRegistry);
        try {
            log.info("Fetching weather for: {}", city);
            WeatherResponse response = weatherService.getCurrentWeather(city);
            sample.stop(Timer.builder("weather.tool.duration")
                    .tag("city", city)
                    .register(meterRegistry));
            return response;
        } catch (Exception e) {
            log.error("Error fetching weather for {}", city, e);
            throw new ToolExecutionException("Unable to fetch weather data", e);
        }
    }

    @Tool(description = "Get 5-day weather forecast for a city")
    public ForecastResponse getForecast(
            @ToolParam("City name") String city,
            @ToolParam(value = "Temperature unit (celsius or fahrenheit)", required = false)
            String unit) {

        String tempUnit = unit != null ? unit : "celsius";
        return weatherService.getForecast(city, tempUnit);
    }

    @Tool(description = "Get weather alerts for a location")
    public List<WeatherAlert> getWeatherAlerts(
            @ToolParam("State or province code (e.g., 'CA', 'NY')") String stateCode) {

        return weatherService.getAlerts(stateCode);
    }
}

// WeatherService.java
@Service
public class WeatherService {

    private final WebClient webClient;
    private final WeatherCache cache;

    public WeatherService(WebClient.Builder webClientBuilder,
                         WeatherCache cache) {
        this.webClient = webClientBuilder
                .baseUrl("https://api.weather.gov")
                .build();
        this.cache = cache;
    }

    @Cacheable(value = "weather", key = "#city")
    public WeatherResponse getCurrentWeather(String city) {
        return webClient.get()
                .uri("/points/{city}/forecast", city)
                .retrieve()
                .bodyToMono(WeatherResponse.class)
                .block();
    }
}

Example 2: Database Query MCP Server

@Component
@PreAuthorize("hasRole('USER')")
public class DatabaseTools {

    private final JdbcTemplate jdbcTemplate;
    private final QueryValidator validator;

    public DatabaseTools(JdbcTemplate jdbcTemplate, QueryValidator validator) {
        this.jdbcTemplate = jdbcTemplate;
        this.validator = validator;
    }

    @Tool(description = "Execute a read-only SQL query and return results")
    public QueryResult executeQuery(
            @ToolParam("SQL SELECT query to execute") String sql,
            @ToolParam(value = "Query parameters as JSON map", required = false)
            String paramsJson) {

        // Validate query is read-only
        validator.validateReadOnly(sql);

        // Parse parameters
        Map<String, Object> params = parseParams(paramsJson);

        // Execute with timeout
        return jdbcTemplate.query(sql, params, rs -> {
            ResultSetMetaData metaData = rs.getMetaData();
            int columnCount = metaData.getColumnCount();
            List<Map<String, Object>> rows = new ArrayList<>();

            while (rs.next()) {
                Map<String, Object> row = new LinkedHashMap<>();
                for (int i = 1; i <= columnCount; i++) {
                    row.put(metaData.getColumnName(i), rs.getObject(i));
                }
                rows.add(row);
            }

            return new QueryResult(rows, rows.size());
        });
    }

    @Tool(description = "Get table metadata including columns and types")
    public TableMetadata describeTable(
            @ToolParam("Table name") String tableName) {

        String sql = """
            SELECT column_name, data_type, is_nullable, column_default
            FROM information_schema.columns
            WHERE table_name = ?
            ORDER BY ordinal_position
            """;

        List<ColumnInfo> columns = jdbcTemplate.query(sql,
                (rs, rowNum) -> new ColumnInfo(
                        rs.getString("column_name"),
                        rs.getString("data_type"),
                        rs.getString("is_nullable").equals("YES"),
                        rs.getString("column_default")
                ),
                tableName
        );

        return new TableMetadata(tableName, columns);
    }
}

Example 3: File Operations MCP Server

@Component
@Slf4j
public class FileSystemTools {

    private final Path basePath;
    private final FileSecurityFilter securityFilter;

    public FileSystemTools(
            @Value("${mcp.file.base-path:/tmp}") String basePath,
            FileSecurityFilter securityFilter) {
        this.basePath = Paths.get(basePath).normalize();
        this.securityFilter = securityFilter;
    }

    @Tool(description = "List files in a directory")
    public List<FileInfo> listFiles(
            @ToolParam(value = "Directory path (relative to base)", required = false)
            String directory) {

        Path targetPath = resolvePath(directory != null ? directory : "");
        securityFilter.validatePath(targetPath, basePath);

        try (Stream<Path> stream = Files.list(targetPath)) {
            return stream
                    .filter(Files::isRegularFile)
                    .map(this::toFileInfo)
                    .toList();
        } catch (IOException e) {
            throw new ToolExecutionException("Failed to list files", e);
        }
    }

    @Tool(description = "Read file contents")
    public FileContent readFile(
            @ToolParam("File path (relative to base)") String filePath,
            @ToolParam(value = "Maximum lines to read", required = false)
            Integer maxLines) {

        Path targetPath = resolvePath(filePath);
        securityFilter.validatePath(targetPath, basePath);

        try {
            List<String> lines = maxLines != null
                    ? Files.lines(targetPath).limit(maxLines).toList()
                    : Files.readAllLines(targetPath);

            return new FileContent(targetPath.toString(), lines);
        } catch (IOException e) {
            throw new ToolExecutionException("Failed to read file", e);
        }
    }

    @Tool(description = "Search for files matching a pattern")
    public List<FileInfo> searchFiles(
            @ToolParam("Search pattern (glob, e.g., '*.txt')") String pattern,
            @ToolParam(value = "Directory to search in", required = false)
            String directory) {

        Path targetPath = resolvePath(directory != null ? directory : "");
        securityFilter.validatePath(targetPath, basePath);

        try (Stream<Path> stream = Files.walk(targetPath, 10)) {
            PathMatcher matcher = FileSystems.getDefault()
                    .getPathMatcher("glob:" + pattern);

            return stream
                    .filter(Files::isRegularFile)
                    .filter(path -> matcher.matches(path.getFileName()))
                    .map(this::toFileInfo)
                    .toList();
        } catch (IOException e) {
            throw new ToolExecutionException("Search failed", e);
        }
    }

    private Path resolvePath(String relativePath) {
        return basePath.resolve(relativePath).normalize();
    }

    private FileInfo toFileInfo(Path path) {
        try {
            return new FileInfo(
                    basePath.relativize(path).toString(),
                    Files.size(path),
                    Files.getLastModifiedTime(path).toInstant()
            );
        } catch (IOException e) {
            return new FileInfo(path.toString(), 0, Instant.now());
        }
    }
}

Example 4: REST API Integration MCP Server

@Component
@Slf4j
public class ApiIntegrationTools {

    private final WebClient webClient;
    private final ApiCredentialManager credentialManager;

    public ApiIntegrationTools(WebClient.Builder webClientBuilder,
                              ApiCredentialManager credentialManager) {
        this.webClient = webClientBuilder.build();
        this.credentialManager = credentialManager;
    }

    @Tool(description = "Call an external REST API endpoint")
    public ApiResponse callExternalApi(
            @ToolParam("HTTP method (GET, POST, PUT, DELETE)") String method,
            @ToolParam("API URL") String url,
            @ToolParam(value = "Request body (JSON)", required = false)
            String body,
            @ToolParam(value = "Headers (JSON map)", required = false)
            String headersJson) {

        // Validate URL
        validateUrl(url);

        // Get credentials
        ApiCredentials credentials = credentialManager.getCredentials(url);

        // Build request
        WebClient.RequestBodySpec request = webClient
                .method(HttpMethod.valueOf(method.toUpperCase()))
                .uri(url);

        // Add headers
        addHeaders(request, headersJson, credentials);

        // Add body if applicable
        if (body != null && !body.isBlank()) {
            request.contentType(MediaType.APPLICATION_JSON);
            request.body(body);
        }

        // Execute
        return request.retrieve()
                .bodyToMono(ApiResponse.class)
                .block();
    }

    @Tool(description = "Paginate through API results")
    public List<ApiResponse> fetchPaginatedResults(
            @ToolParam("Base API URL") String baseUrl,
            @ToolParam(value = "Page size", required = false)
            Integer pageSize) {

        int size = pageSize != null ? pageSize : 100;
        List<ApiResponse> allResults = new ArrayList<>();
        int page = 0;

        while (true) {
            String url = baseUrl + "?page=" + page + "&size=" + size;
            PaginatedResponse response = webClient.get()
                    .uri(url)
                    .retrieve()
                    .bodyToMono(PaginatedResponse.class)
                    .block();

            allResults.addAll(response.getData());

            if (!response.hasNext()) {
                break;
            }
            page++;
        }

        return allResults;
    }
}

Example 5: Prompt Template MCP Server

@Component
public class CodeReviewPrompts {

    @PromptTemplate(
        name = "java-code-review",
        description = "Review Java code for best practices and potential issues"
    )
    public Prompt createCodeReviewPrompt(
            @PromptParam("Java code to review") String code,
            @PromptParam(value = "Focus areas (comma-separated)", required = false)
            String focusAreas) {

        String focus = focusAreas != null ? focusAreas : "general best practices";

        return Prompt.builder()
                .system(createSystemPrompt())
                .user(createUserPrompt(code, focus))
                .build();
    }

    @PromptTemplate(
        name = "refactor-suggestion",
        description = "Suggest refactoring improvements for code"
    )
    public Prompt createRefactorPrompt(
            @PromptParam("Code to refactor") String code,
            @PromptParam("Refactoring goal") String goal) {

        return Prompt.builder()
                .system("You are an expert software architect specializing in code refactoring.")
                .user("""
                    Analyze the following code and suggest refactoring to achieve: {goal}

                    ```java
                    {code}
                    ```

                    Provide:
                    1. Current issues identified
                    2. Suggested refactoring approach
                    3. Refactored code example
                    4. Benefits of the refactoring
                    """.replace("{code}", code).replace("{goal}", goal))
                .build();
    }

    private String createSystemPrompt() {
        return """
            You are an expert Java code reviewer with 20 years of experience.
            Focus on:
            - Code correctness and potential bugs
            - Performance optimizations
            - Security vulnerabilities
            - SOLID principles adherence
            - Clean code practices
            - Design pattern usage
            """;
    }

    private String createUserPrompt(String code, String focus) {
        return """
            Review the following Java code with focus on: {focus}

            ```java
            {code}
            ```

            Format your response as:
            ## Critical Issues (Must Fix)
            ## Warnings (Should Fix)
            ## Suggestions (Consider Improving)
            ## Positive Aspects
            """.replace("{code}", code).replace("{focus}", focus);
    }
}

Example 6: Application Configuration

# application.yml
spring:
  application:
    name: weather-mcp-server
  ai:
    openai:
      api-key: ${OPENAI_API_KEY}
      chat:
        options:
          model: gpt-4o-mini
          temperature: 0.7
    mcp:
      enabled: true
      server:
        name: weather-mcp-server
        version: 1.0.0
      transport:
        type: stdio  # or http, sse
        http:
          port: 8080
          path: /mcp
          cors:
            enabled: true
            allowed-origins: "*"
      security:
        enabled: true
        authorization:
          mode: role-based
          default-deny: true
        audit:
          enabled: true
      tools:
        package-scan: com.example.mcp.tools
        validation:
          enabled: true
          max-execution-time: 30s
        caching:
          enabled: true
          ttl: 5m
      actuator:
        enabled: true

management:
  endpoints:
    web:
      exposure:
        include: health,info,metrics,prometheus
  endpoint:
    health:
      show-details: always
  metrics:
    export:
      prometheus:
        enabled: true

logging:
  level:
    com.example.mcp: DEBUG
    org.springframework.ai: INFO

API Reference

For comprehensive examples, see examples.md including:

• Basic MCP server setup
• Multi-tool enterprise servers
• Secure tool implementations
• Integration with Spring Data
• Real-time data streaming
• Multi-modal applications

Complete API documentation is available in api-reference.md covering:

• Core annotations and interfaces
• Configuration properties
• Transport implementations
• Security integrations
• Testing utilities

References

• Spring AI Documentation
• Model Context Protocol Specification
• LangChain4j MCP Patterns
• Spring Boot Documentation

Constraints and Warnings

Security Constraints

• Never Expose Sensitive Data: Tool descriptions, parameter names, and error messages must not contain passwords, API keys, or confidential information.

• Input Validation is Mandatory: Always validate and sanitize inputs. AI models may generate malicious or malformed parameters intentionally or unintentionally.

• SQL Injection Prevention: For database tools, use parameterized queries exclusively. Never concatenate strings into SQL statements.

• Path Traversal Prevention: For file system tools, validate and normalize all paths to prevent directory traversal attacks (e.g., ../../etc/passwd).

• Authorization Required: Every tool should verify that the current user has permission to perform the requested action.

Operational Constraints

• Idempotency: Tools should be idempotent when possible as AI models may retry failed calls. Non-idempotent operations should clearly document this behavior.

• Timeout Handling: All tools must implement proper timeout handling to prevent hanging requests. The default timeout should be configurable.

• Resource Limits: Implement limits on resource usage (memory, CPU, network) to prevent denial-of-service through resource exhaustion.

• Rate Limiting: Rate limiting should be implemented to prevent abuse of expensive operations. Different tools may have different rate limits.

• Concurrent Execution: Consider thread safety for tools that may be called concurrently. Use appropriate synchronization.

AI Model Constraints

• Context Window Limits: Tool responses should be concise. Large responses can exceed context window limits, causing the AI model to truncate or ignore information.

• Response Format: Use structured data (JSON, records) for responses to help AI models parse and understand results.

• Description Quality: Tool and parameter descriptions are critical for AI model understanding. Poor descriptions lead to incorrect tool usage.

• Tool Naming: Tool names should be self-describing and avoid abbreviations that might confuse AI models.

Performance Constraints

• Caching Considerations: Be aware that caching can return stale data. Implement cache invalidation for dynamic data.

• Memory Management: Dynamic tool registration can cause memory leaks if tools are not properly unregistered. Implement cleanup procedures.

• Connection Pooling: Configure appropriate connection pool sizes to avoid resource exhaustion.

Multi-Model Constraints

• Model-Specific Capabilities: Multi-model configurations require careful management of model-specific capabilities. Not all models support all features.

• Compatibility: Ensure tool responses are compatible with all configured AI models. Avoid model-specific features unless necessary.

Spring AI Specific Warnings

• Version Compatibility: Spring AI is actively developed. API changes may occur between versions. Pin specific versions in production.

• Transport Selection: Choose the appropriate transport (stdio, HTTP, SSE) for your use case. Each has different performance and security characteristics.

• Error Propagation: Exceptions thrown by tools are exposed to AI models. Ensure error messages don't leak sensitive information.

Deployment Constraints

• Health Checks: Implement health checks that verify tool availability and connectivity to external services.

• Configuration Management: Use environment variables or secure vaults for sensitive configuration values. Never hardcode credentials.

• Monitoring: Implement comprehensive monitoring for tool usage, execution times, and error rates.

• Graceful Shutdown: Ensure tools can complete in-progress operations when the server is shutting down.