spring-ai-mcp-server-patterns
npx skills add https://github.com/giuseppe-trisciuoglio/developer-kit --skill spring-ai-mcp-server-patterns
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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
@Toolannotation - Resources: Data sources accessible through MCP endpoints
- Prompts: Reusable prompt templates with
@PromptTemplateannotation - 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
- Add Spring AI MCP dependencies to your
pom.xmlorbuild.gradle - Configure the AI model (OpenAI, Anthropic, etc.) in
application.properties - Enable MCP server with
@EnableMcpServerannotation
2. Define Tools
- Create a Spring component class (
@Component) - Annotate methods with
@Tool(description = "...") - Use
@ToolParamto document parameters for AI understanding - Implement business logic with proper error handling
3. Create Prompt Templates
- Create prompt template components
- Use
@PromptTemplatefor reusable prompts - Define parameters with
@PromptParam - Return
Promptobjects with system and user messages
4. Configure Transport
- Choose transport type:
stdio,http, orsse - Configure transport properties in
application.yml - Set up CORS if using HTTP/SSE
5. Add Security
- Implement Spring Security configuration
- Create tool filters for role-based access control
- Add input validation to prevent injection attacks
- Implement audit logging for sensitive operations
6. Testing
- Write unit tests for individual tools
- Create integration tests for MCP endpoints
- Test security configurations
- Use Testcontainers for database-dependent tools
7. Deployment
- Configure actuator endpoints for health checks
- Set up metrics and monitoring
- Implement rate limiting for production
- 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
@Toolannotation - Resources: Data sources accessible via Spring components
- Prompts: Template-based interactions with
@PromptTemplate - Transport: Spring-managed communication channels
AI Application ââ MCP Client ââ Spring AI ââ MCP Server ââ 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
-
Use Declarative Annotations: Prefer
@Tooland@PromptTemplateover manual registration for cleaner, more maintainable code. -
Keep Tools Focused: Each tool should do one thing well. Avoid creating monolithic tools that handle multiple unrelated operations.
-
Use Descriptive Names: Tool names should clearly indicate what they do. Use verbs like
get,create,update,delete,searchfor actions. -
Document Parameters: Use
@ToolParamwith clear descriptions so AI models understand when and how to use each parameter. -
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
-
Implement Input Validation: Always validate user inputs to prevent injection attacks. Never trust AI-generated parameters without validation.
-
Use Authorization: Implement role-based access control for sensitive operations. Use Spring Security annotations like
@PreAuthorize. -
Sanitize Error Messages: Never expose sensitive information in error messages or tool descriptions.
-
Audit Sensitive Operations: Log all executions of tools that modify data or access sensitive resources.
-
Rate Limiting: Implement rate limiting for expensive operations to prevent abuse and ensure fair usage.
Performance Optimization
-
Use Caching: Cache results of expensive operations using Spring Cache with
@Cacheable. Set appropriate TTL values. -
Implement Timeouts: Always set timeouts for external API calls to prevent hanging requests.
-
Use Async Processing: For long-running operations, consider using
@Asyncto return immediately and provide status updates. -
Connection Pooling: Configure proper connection pools for database and HTTP clients.
-
Monitor Performance: Track tool execution times and success rates using Micrometer metrics.
Error Handling
-
Handle Errors Gracefully: Implement proper exception handling with user-friendly error messages.
-
Use Specific Exceptions: Create custom exceptions for different error scenarios to enable proper error handling.
-
Implement Fallback: Provide fallback values or retry logic for transient failures.
-
Log Context: Include relevant context (user, tool name, parameters) in error logs for debugging.
Testing
-
Write Unit Tests: Test each tool independently with mocked dependencies.
-
Write Integration Tests: Test the entire MCP server flow including transport and serialization.
-
Test Security: Verify that authorization rules are properly enforced.
-
Use Testcontainers: For database-dependent tools, use Testcontainers for realistic testing.
-
Test Edge Cases: Test with invalid inputs, null values, and boundary conditions.
Documentation
-
Document Tool Purpose: Clearly describe what each tool does and when to use it.
-
Provide Examples: Include usage examples in the tool description or separate documentation.
-
Version Your API: Maintain backward compatibility when updating tools. Use semantic versioning.
-
Document Return Types: Clearly describe the structure of return values.
Configuration
-
Externalize Configuration: Use
application.ymlfor configurable values like URLs, timeouts, and credentials. -
Use Profiles: Define different configurations for dev, test, and production environments.
-
Validate Configuration: Use
@ConfigurationPropertieswith validation for type-safe configuration.
Spring-Specific Best Practices
-
Leverage Dependency Injection: Use constructor injection for dependencies to improve testability.
-
Use Qualifiers: When multiple beans of the same type exist, use
@Qualifierto disambiguate. -
Implement Health Checks: Provide health indicators to monitor MCP server status.
-
Use Profiles: Different configurations for development and production environments.
AI-Specific Considerations
-
Design for Idempotency: Tools should be idempotent when possible as AI models may retry failed calls.
-
Be Conservative with Data Modifying Tools: AI models may call modifying tools unexpectedly – consider adding confirmation steps.
-
Provide Context: Include relevant context in responses to help AI models understand results.
-
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
@Toolinstead 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
FunctionCallbackfor low-level control
Migration Steps
- Replace LangChain4j
@ToolMethodwith Spring AI@Tool - Update configuration from
application.propertiesto Spring AI properties - Migrate tool providers to Spring components with
@Component - Update prompt templates to use Spring AI’s prompt abstractions
- 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.