Breaking Changes in 0.8.0 ⚠️

Note: Version 0.8.0 introduces several breaking changes including a new session-based architecture. If you’re upgrading from 0.7.0, please refer to the Migration Guide for detailed instructions.

Overview

The MCP Server is a foundational component in the Model Context Protocol (MCP) architecture that provides tools, resources, and capabilities to clients. It implements the server-side of the protocol, responsible for:

  • Exposing tools that clients can discover and execute
  • Managing resources with URI-based access patterns
  • Providing prompt templates and handling prompt requests
  • Supporting capability negotiation with clients
  • Implementing server-side protocol operations
  • Managing concurrent client connections
  • Providing structured logging and notifications

The Spring-AI MCP Server integration extends the MCP Java SDK to provide auto-configuration for MCP servdr functionality in Spring Boot applications.

The server supports both synchronous and asynchronous APIs, allowing for flexible integration in different application contexts.

// Create a server with custom configuration
McpSyncServer syncServer = McpServer.sync(transportProvider)
    .serverInfo("my-server", "1.0.0")
    .capabilities(ServerCapabilities.builder()
        .resources(true)     // Enable resource support
        .tools(true)         // Enable tool support
        .prompts(true)       // Enable prompt support
        .logging()           // Enable logging support
        .build())
    .build();

// Register tools, resources, and prompts
syncServer.addTool(syncToolSpecification);
syncServer.addResource(syncResourceSpecification);
syncServer.addPrompt(syncPromptSpecification);

// Send logging notifications
syncServer.loggingNotification(LoggingMessageNotification.builder()
    .level(LoggingLevel.INFO)
    .logger("custom-logger")
    .data("Server initialized")
    .build());

// Close the server when done
syncServer.close();

Server Transport Providers

The transport layer in the MCP SDK is responsible for handling the communication between clients and servers. It provides different implementations to support various communication protocols and patterns. The SDK includes several built-in transport provider implementations:

Create in-process based transport:

StdioServerTransportProvider transportProvider = new StdioServerTransportProvider(new ObjectMapper());

Provides bidirectional JSON-RPC message handling over standard input/output streams with non-blocking message processing, serialization/deserialization, and graceful shutdown support.

Key features:

  • Bidirectional communication through stdin/stdout
  • Process-based integration support
  • Simple setup and configuration
  • Lightweight implementation

Server Capabilities

The server can be configured with various capabilities:

var capabilities = ServerCapabilities.builder()
    .resources(false, true)  // Resource support with list changes notifications
    .tools(true)            // Tool support with list changes notifications
    .prompts(true)          // Prompt support with list changes notifications
    .logging()              // Enable logging support (enabled by default with loging level INFO)
    .build();

Logging Support

The server provides structured logging capabilities that allow sending log messages to clients with different severity levels:

// Send a log message to clients
server.loggingNotification(LoggingMessageNotification.builder()
    .level(LoggingLevel.INFO)
    .logger("custom-logger")
    .data("Custom log message")
    .build());

Clients can control the minimum logging level they receive through the mcpClient.setLoggingLevel(level) request. Messages below the set level will be filtered out. Supported logging levels (in order of increasing severity): DEBUG (0), INFO (1), NOTICE (2), WARNING (3), ERROR (4), CRITICAL (5), ALERT (6), EMERGENCY (7)

Tool Specification

The Model Context Protocol allows servers to expose tools that can be invoked by language models. The Java SDK allows implementing a Tool Specifications with their handler functions. Tools enable AI models to perform calculations, access external APIs, query databases, and manipulate files:

// Sync tool specification
var schema = """
            {
              "type" : "object",
              "id" : "urn:jsonschema:Operation",
              "properties" : {
                "operation" : {
                  "type" : "string"
                },
                "a" : {
                  "type" : "number"
                },
                "b" : {
                  "type" : "number"
                }
              }
            }
            """;
var syncToolSpecification = new McpServerFeatures.SyncToolSpecificaiton(
    new Tool("calculator", "Basic calculator", schema),
    (exchange, arguments) -> {
        // Tool implementation
        return new CallToolResult(result, false);
    }
);

The Tool specification includes a Tool definition with name, description, and parameter schema followed by a call handler that implements the tool’s logic. The function’s first argument is McpAsyncServerExchange for client interaction, and the second is a map of tool arguments.

Resource Specification

Specification of a resource with its handler function. Resources provide context to AI models by exposing data such as: File contents, Database records, API responses, System information, Application state. Example resource specification:

// Sync resource specification
var syncResourceSpecification = new McpServerFeatures.syncResourceSpecification(
    new Resource("custom://resource", "name", "description", "mime-type", null),
    (exchange, request) -> {
        // Resource read implementation
        return new ReadResourceResult(contents);
    }
);

The resource specification compriese of resource definitions and resource read handler. The resource definition including name, description, and MIME type. The first argument of the function that handles resource read requests is an McpAsyncServerExchange upon which the server can interact with the connected client. The second arguments is a McpSchema.ReadResourceRequest.

Prompt Specification

As part of the Prompting capabilities, MCP provides a standardized way for servers to expose prompt templates to clients. The Prompt Specification is a structured template for AI model interactions that enables consistent message formatting, parameter substitution, context injection, response formatting, and instruction templating.

// Sync prompt specification
var syncPromptSpecification = new McpServerFeatures.syncPromptSpecification(
    new Prompt("greeting", "description", List.of(
        new PromptArgument("name", "description", true)
    )),
    (exchange, request) -> {
        // Prompt implementation
        return new GetPromptResult(description, messages);
    }
);

The prompt definition includes name (identifier for the prompt), description (purpose of the prompt), and list of arguments (parameters for templating). The handler function processes requests and returns formatted templates. The first argument is McpAsyncServerExchange for client interaction, and the second argument is a GetPromptRequest instance.

Using Sampling from a Server

To use Sampling capabilities, connect to a client that supports sampling. No special server configuration is needed, but verify client sampling support before making requests. Learn about client sampling support.

Once connected to a compatible client, the server can request language model generations:

// Create a server
McpSyncServer server = McpServer.sync(transportProvider)
    .serverInfo("my-server", "1.0.0")
    .build();

// Define a tool that uses sampling
var calculatorTool = new McpServerFeatures.SyncToolSpecification(
    new Tool("ai-calculator", "Performs calculations using AI", schema),
    (exchange, arguments) -> {
        // Check if client supports sampling
        if (exchange.getClientCapabilities().sampling() == null) {
            return new CallToolResult("Client does not support AI capabilities", false);
        }
        
        // Create a sampling request
        McpSchema.CreateMessageRequest request = McpSchema.CreateMessageRequest.builder()
            .content(new McpSchema.TextContent("Calculate: " + arguments.get("expression")))
            .modelPreferences(McpSchema.ModelPreferences.builder()
                .hints(List.of(
                    McpSchema.ModelHint.of("claude-3-sonnet"),
                    McpSchema.ModelHint.of("claude")
                ))
                .intelligencePriority(0.8)  // Prioritize intelligence
                .speedPriority(0.5)         // Moderate speed importance
                .build())
            .systemPrompt("You are a helpful calculator assistant. Provide only the numerical answer.")
            .maxTokens(100)
            .build();
        
        // Request sampling from the client
        McpSchema.CreateMessageResult result = exchange.createMessage(request);
        
        // Process the result
        String answer = result.content().text();
        return new CallToolResult(answer, false);
    }
);

// Add the tool to the server
server.addTool(calculatorTool);

The CreateMessageRequest object allows you to specify: Content - the input text or image for the model, Model Preferences - hints and priorities for model selection, System Prompt - instructions for the model’s behavior and Max Tokens - maximum length of the generated response.

Error Handling

The SDK provides comprehensive error handling through the McpError class, covering protocol compatibility, transport communication, JSON-RPC messaging, tool execution, resource management, prompt handling, timeouts, and connection issues. This unified error handling approach ensures consistent and reliable error management across both synchronous and asynchronous operations.

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