== MCP

https://modelcontextprotocol.io/[Model Context Protocol (MCP)] module for Jooby.

The MCP module provides seamless integration with the Model Context Protocol, allowing your application to act as a standardized AI context server. It automatically bridges your Java/Kotlin methods with LLM clients by exposing them as Tools, Resources, and Prompts.

=== Usage

1) Add the dependencies (Jooby MCP, Jackson, and the APT processor):

[dependency, artifactId="jooby-jackson3:Jackson Module, jooby-mcp-jackson3:MCP Jackson Module, jooby-mcp:MCP Module"]
.

[NOTE]
====
You must configure the Jooby Annotation Processor (APT) in your build. The MCP module relies on APT to generate high-performance routing code with zero reflection overhead.
====

2) Define a service and expose capabilities via annotations:

.Java
[source, java, role="primary"]
----
import io.jooby.annotation.mcp.McpTool;

public class CalculatorService {

  @McpTool(description = "Adds two numbers together")
  public int add(int a, int b) {
    return a + b;
  }
}
----

.Kotlin
[source, kt, role="secondary"]
----
import io.jooby.annotation.mcp.McpTool

class CalculatorService {

  @McpTool(description = "Adds two numbers together")
  fun add(a: Int, b: Int): Int {
    return a + b
  }
}
----

3) Install the module using Jackson and the generated service:

.Java
[source, java, role="primary"]
----
import io.jooby.jackson3.Jackson3Module;
import io.jooby.mcp.jackson3.McpJackson3Module;
import io.jooby.mcp.McpModule;

{
  install(new Jackson3Module());                               <1>

  install(new McpJackson3Module());                            <2>

  install(new McpModule(new CalculatorServiceMcp_()));         <3>
}
----

.Kotlin
[source, kt, role="secondary"]
----
import io.jooby.jackson3.Jackson3Module
import io.jooby.mcp.jackson3.McpJackson3Module
import io.jooby.mcp.McpModule

{
  install(Jackson3Module())                                    <1>

  install(McpJackson3Module())                                 <2>

  install(McpModule(CalculatorServiceMcp_()))                  <3>
}
----

<1> Install JSON support (Jackson is required for MCP JSON-RPC serialization). For Jackson 2, use `JacksonModule()` instead.
<2> Install MCP JSON support. For Jackson 2, use `McpJackson2Module()` instead.
<3> Install the MCP module with the APT-generated `McpService` dispatcher. The generated class always ends with the `Mcp_` suffix.

=== Core Capabilities

The module uses annotations to expose application logic to AI clients:

- `@McpTool`: Exposes a method as an executable tool. The module automatically generates JSON schemas for the parameters.
- `@McpPrompt`: Exposes a method as a reusable prompt template.
- `@McpResource` / `@McpResourceTemplate`: Exposes static or dynamic data as an MCP resource (e.g., `file://config`).
- `@McpCompletion`: Handles auto-completion logic for prompts and resources.

=== Schema Descriptions & Javadoc

Rich descriptions are highly recommended for LLM usage so the model understands exactly what a tool, prompt, or resource does. You can provide these descriptions directly in the MCP annotations (e.g., `@McpTool(description = "...")`).

However, if you omit them, the Jooby Annotation Processor will automatically extract descriptions from your standard Javadoc comments, including method descriptions and `@param` tags.

.Javadoc Extraction Example
[source, java]
----
import io.jooby.annotation.mcp.McpTool;

public class WeatherService {

  /**
   * Retrieves the current weather forecast for a given location.
   *
   * @param location The city and state, e.g., "San Francisco, CA"
   * @param units The temperature unit to use (celsius or fahrenheit)
   */
  @McpTool
  public WeatherForecast getWeather(String location, String units) {
    // ...
  }
}
----

In the example above, the LLM will automatically receive the method's Javadoc summary as the tool description, and the `@param` comments as the descriptions for the `location` and `units` JSON schema properties.

=== Transports

By default, the MCP module starts a single server using the `STREAMABLE_HTTP` transport. You can easily switch to other supported transports such as `SSE` (Server-Sent Events), `WEBSOCKET`, or `STATELESS_STREAMABLE_HTTP`.

.Changing Transport
[source, java]
----
import io.jooby.mcp.McpModule.Transport;

{
  install(new McpModule(new CalculatorServiceMcp_())
      .transport(Transport.WEBSOCKET));
}
----

=== Output Schema Generation

By default, the framework does *not* generate JSON output schemas for tools in order to save LLM context window tokens. You can enable it globally on the module, or override it per-method using the `@McpOutputSchema` annotation.

.Programmatic Global Configuration
[source, java]
----
{
   // Enable output schema generation for all tools by default
   install(new McpModule(new CalculatorServiceMcp_())
       .generateOutputSchema(true));
}
----

Alternatively, you can control output schema generation using your application configuration properties. Configuration properties always take precedence over the programmatic setup, and allow you to configure behavior per-server.

.application.conf
[source, properties]
----
# Global fallback for all servers
mcp.generateOutputSchema = true

# Per-server override (takes precedence over the global flag)
mcp.calculator.generateOutputSchema = false
----

You can explicitly override the global/config flag and bypass Java type erasure using nested `@McpOutputSchema` annotations:

.Per-Method Override
[source, java]
----
import io.jooby.annotation.mcp.McpTool;
import io.jooby.annotation.mcp.McpOutputSchema;

public class UserService {

  @McpTool
  @McpOutputSchema.ArrayOf(User.class)          <1>
  public List<Object> findUsers(String query) {
    // ...
  }

  @McpTool
  @McpOutputSchema.Off                          <2>
  public HugeDataset getBigData() {
    // ...
  }
}
----

<1> Forces array schema generation for `User`, overriding generic `Object` erasure and the global/config flag.
<2> Explicitly disables schema generation for this specific tool.

=== Custom Invokers & Telemetry

You can inject custom logic (like SLF4J MDC context propagation, tracing, or custom error handling) around every tool, prompt, or resource execution by providing an `McpInvoker`.

[NOTE]
====
Invokers are chained. You can register multiple invokers and they will wrap the execution in the order they were added:
`install(new McpModule(...).invoker(new LoggingInvoker()).invoker(new SecurityInvoker()));`
====

.MDC Invoker Example
[source, java]
----
import io.jooby.mcp.McpInvoker;
import io.jooby.mcp.McpOperation;
import org.slf4j.MDC;

public class MdcMcpInvoker implements McpInvoker {
  @Override
  public <R> R invoke(McpOperation operation, SneakyThrows.Supplier<R> action) {
    try {
      MDC.put("mcp.id", operation.id());                 <1>
      MDC.put("mcp.class", operation.className());
      MDC.put("mcp.method", operation.methodName());
      return action.get();                               <2>
    } finally {
      MDC.remove("mcp.id");
      MDC.remove("mcp.class");
      MDC.remove("mcp.method");
    }
  }
}

{
  install(new McpModule(new CalculatorServiceMcp_())
      .invoker(new MdcMcpInvoker()));                    <3>
}
----

<1> Extract rich contextual data from the `McpOperation` record.
<2> Proceed with the execution chain.
<3> Register the invoker. Jooby will safely map any business exceptions thrown by your action into valid MCP JSON-RPC errors.

=== Multiple Servers

You can run multiple, completely isolated MCP server instances within the same Jooby application by utilizing the `@McpServer("serverName")` annotation on your service classes.

When bootstrapping multiple servers, you *must* provide configuration for each server in your `application.conf`.

.application.conf
[source, properties]
----
mcp.default.name = "default-mcp-server"
mcp.default.version = "1.0.0"

mcp.calculator.name = "calculator-mcp-server"
mcp.calculator.version = "1.0.0"
mcp.calculator.transport = "sse"
mcp.calculator.mcpEndpoint = "/mcp/calculator/sse"
----

.Java Bootstrap
[source, java]
----
{
  // Bootstraps services each on their corresponding service base based on the @McpServer mappings
  install(new McpModule(
      new DefaultServiceMcp_(), 
      new CalculatorServiceMcp_()
  ));
}
----

=== Debugging & Testing (MCP Inspector)

When building an MCP server, it is highly recommended to test your tools, prompts, and resources locally before connecting them to a real LLM client.

The `McpInspectorModule` provides a built-in, interactive web UI that acts as a dummy LLM client. It allows you to manually trigger tools, view generated output schemas, inspect resources, and debug JSON-RPC payloads in real-time.

1) Add the inspector dependency (typically as a `test` or `development` dependency):

[dependency, artifactId="jooby-mcp-inspector:MCP Inspector"]
.

2) Install the module, ensuring it is only active during development:

.Java Bootstrap
[source, java, role="primary"]
----
import io.jooby.mcp.McpModule;
import io.jooby.mcp.inspector.McpInspectorModule;

{
  install(new McpModule(
      new DefaultServiceMcp_(),
      new CalculatorServiceMcp_()
  ));

  // Only enable the inspector UI in the 'dev' environment
  if (getEnvironment().isActive("dev")) {
    install(new McpInspectorModule());
  }
}
----

.Kotlin
[source, kt, role="secondary"]
----
import io.jooby.mcp.McpModule
import io.jooby.mcp.inspector.McpInspectorModule

{
  install(McpModule(
      DefaultServiceMcp_(),
      CalculatorServiceMcp_()
  ))

  // Only enable the inspector UI in the 'dev' environment
  if (environment.isActive("dev")) {
    install(McpInspectorModule())
  }
}
----

Once the application starts, open your browser and navigate to the default inspector route: `http://localhost:8080/mcp-inspector`.

==== Inspector Configuration

You can customize the behavior and mounting point of the Inspector UI using its programmatic builder methods:

.Programmatic Setup
[source, java, role="primary"]
----
{
  if (getEnvironment().isActive("dev")) {
    install(new McpInspectorModule()
        .path("/debug/mcp")                           <1>
        .defaultServer("calculator-mcp-server")       <2>
        .autoConnect(true)                            <3>
    );
  }
}
----

.Kotlin
[source, kt, role="secondary"]
----
{
  if (environment.isActive("dev")) {
    install(McpInspectorModule()
        .path("/debug/mcp")                           <1>
        .defaultServer("calculator-mcp-server")       <2>
        .autoConnect(true)                            <3>
    )
  }
}
----

<1> Changes the base path for the Inspector UI (defaults to `/mcp-inspector`).
<2> Automatically selects a specific named server in the UI dropdown when dealing with multiple MCP servers.
<3> Automatically connects to the selected server as soon as the page loads.

=== Special Thanks

A special thanks to https://github.com/kliushnichenko[kliushnichenko]. This MCP module was heavily inspired by and based upon their foundational work and contributions to the ecosystem.
