Mcp4k

What is Mcp4k

mcp4k is a compiler-driven framework for building clients and servers using the Model Context Protocol (MCP) in Kotlin. It implements most of the MCP specification, including resources, prompts, tools, and sampling.

Use cases

Use cases for mcp4k include building interactive tools, developing server-side applications that expose resources and prompts, and creating client applications that connect to MCP servers for various functionalities.

How to use

To use mcp4k, annotate your functions with @McpTool or @McpPrompt. This will automatically generate JSON-RPC handlers, schema metadata, and a complete lifecycle framework. Add mcp4k to your build using the specified Gradle configuration.

Key features

Key features of mcp4k include automatic generation of JSON-RPC handlers, compile-time parameter type enforcement, support for multiple transports (like stdio and HTTP-SSE), and comprehensive lifecycle management.

Where to use

mcp4k can be used in any application that requires communication between clients and servers via the Model Context Protocol, particularly in Kotlin Multiplatform projects.

mcp4k is a compiler-driven framework for building both clients and servers using the
Model Context Protocol (MCP) in Kotlin.
It implements the vast majority of the MCP specification, including resources, prompts, tools, sampling, and more.

mcp4k automatically generates JSON-RPC handlers, schema metadata, and manages the complete lifecycle for you.

---

Overview

• Client: Connects to any MCP server to request prompts, read resources, or invoke tools.
• Server: Exposes resources, prompts, and tools to MCP-compatible clients, handling standard JSON-RPC messages and protocol events.
• Transports: Supports stdio, with HTTP-Streaming and other transports on the roadmap.
• Lifecycle: Manages initialization, cancellation, sampling, progress tracking, and more.

mcp4k also enforces correct parameter typing at compile time.
If you describe a tool parameter incorrectly, you get a compile-time error instead of a runtime mismatch.

---

Installation

Add mcp4k to your build:

plugins {
  kotlin("multiplatform") version "2.1.0" // or kotlin("jvm")
  kotlin("plugin.serialization") version "2.1.0"

  id("sh.ondr.mcp4k") version "0.4.1" // <-- Add this
}

---

Quick Start

Create a Simple Server

/**
 * Reverses an input string
 *
 * @param input The string to be reversed
 */
@McpTool
fun reverseString(input: String): ToolContent {
  return "Reversed: ${input.reversed()}".toTextContent()
}

fun main() = runBlocking {
  val server = Server.Builder()
    .withTool(::reverseString)
    .withTransport(StdioTransport())
    .build()
    
  server.start()
  
  // Keep server running 
  while (true) { 
    delay(1000)
  }
}

In this example, your new @McpTool is exposed via JSON-RPC as reverseString.
Clients can call it by sending tools/call messages.

---

Create a Simple Client

fun main() = runBlocking {
  val client = Client.Builder()
    .withClientInfo("MyClient", "1.0.0")
    .withTransport(StdioTransport())
    .build()
  
  client.start()
  client.initialize()
}

All boilerplate (capability negotiation, JSON-RPC ID handling, etc.) is handled by mcp4k.

Once connected, the client can discover prompts/tools/resources and make calls according to the MCP spec:

val allTools = client.getAllTools()
println("Server tools = $allTools")

val response = client.callTool(
  name = "reverseString",
  arguments = buildMap {
    put("input", JsonPrimitive("Some string we want reversed"))
  },
)

val result = response.result?.deserializeResult<CallToolResult>()
println(result) // --> "desrever tnaw ew gnirts emoS"

If you want to get notified when the server changes its tools, you can provide a callback:

val client = Client.Builder()
  // ...
  .withOnToolsChanged { updatedTools: List<Tool> ->
    println("Updated tools: $updatedTools")
  }
  .build()

---

Transport Logging

You can observe raw incoming/outgoing messages by providing withTransportLogger lambdas:

val server = Server.Builder()
  .withTransport(StdioTransport())
  .withTransportLogger(
    logIncoming = { msg -> println("SERVER INCOMING: $msg") },
    logOutgoing = { msg -> println("SERVER OUTGOING: $msg") },
  )
  .build()

Both Server and Client accept this configuration. Super useful for debugging and tests.

---

Tools

Let’s look at a more advanced tool example:

@JsonSchema @Serializable
enum class Priority {
  LOW, NORMAL, HIGH
}

/**
 * @property title The email's title
 * @property body The email's body
 * @property priority The email's priority
 */
@JsonSchema @Serializable
data class Email(
  val title: String,
  val body: String?,
  val priority: Priority = Priority.NORMAL,
)

/**
 * Sends an email
 * @param recipients The email addresses of the recipients
 * @param email The email to send
 */
@McpTool
fun sendEmail(
  recipients: List<String>,
  email: Email,
) = buildString {
  append("Email sent to ${recipients.joinToString()} with ")
  append("title '${email.title}' and ")
  append("body '${email.body}' and ")
  append("priority ${email.priority}")
}.toTextContent()

When clients call tools/list, they see a JSON schema describing the tool’s input:

{
  "type": "object",
  "description": "Sends an email",
  "properties": {
    "recipients": {
      "type": "array",
      "description": "The email addresses of the recipients",
      "items": {
        "type": "string"
      }
    },
    "email": {
      "type": "object",
      "description": "The email to send",
      "properties": {
        "title": {
          "type": "string",
          "description": "The email's title"
        },
        "body": {
          "type": "string",
          "description": "The email's body"
        },
        "priority": {
          "type": "string",
          "description": "The email's priority",
          "enum": [
            "LOW",
            "NORMAL",
            "HIGH"
          ]
        }
      },
      "required": [
        "title"
      ]
    }
  },
  "required": [
    "recipients",
    "email"
  ]
}

KDoc parameter descriptions are type-safe and will throw a compile-time error if you specify a non-existing property. Tool call invocation and type-safe deserialization will be handled by mcp4k.

Server can also add or remove tools at runtime:

server.addTool(::sendEmail)
// ...
server.removeTool(::sendEmail)

Both calls will automatically send ToolListChanged notifications to the client.

Tools can also be added or removed from inside tool functions if they are implemented as Server extension functions:

@McpTool
fun Server.toolThatAddsSecondTool(): ToolContent {
  addTool(::secondTool)
  return "Second tool added!".toTextContent()
}

---

Prompts

Annotate functions with @McpPrompt to define parameterized conversation templates:

@McpPrompt
fun codeReviewPrompt(code: String) = buildPrompt {
  user("Please review the following code:")
  user("'''\n$code\n'''")
}

Clients can call prompts/get to retrieve the underlying messages.

---

Server Context

In some cases, you want multiple tools or prompts to share state. mcp4k allows you to attach a custom context object that tools and prompts can reference.

1. Create a ServerContext object
2. Pass it in with .withContext(...)
3. Each tool or prompt can access it by calling getContextAs()

For example:

// 1) Create your context
class MyServerContext : ServerContext {
  var userName: String = ""
}

// 2) A tool function that writes into the context
@McpTool
fun Server.setUserName(name: String): ToolContent {
  getContextAs<MyServerContext>().userName = name
  return "Username set to: $name".toTextContent()
}

// 3) Another tool that reads from the context
@McpTool
fun Server.greetUser(): ToolContent {
  val name = getContextAs<MyServerContext>().userName
  if (name.isEmpty()) return "No user set yet!".toTextContent()
  return "Hello, $name!".toTextContent()
}

fun main() = runBlocking {
  val context = MyServerContext()
  val server = Server.Builder()
    .withContext(context) // <-- Provide the context
    .withTool(Server::setUserName)
    .withTool(Server::greetUser)
    .withTransport(StdioTransport())
    .build()
  
  server.start()
  while(true) {
    delay(1000)
  }
}

But looking at the above code, it doesn’t make sense that the greetUser function is callable before setUserName has been called.

Thus, we can improve the code by doing:

fun main() {
  val server = Server.Builder()
  // ...
  .withTool(Server::setUserName) // only add this
  // ...
}

@McpTool
fun Server.setUserName(name: String): ToolContent {
  getContextAs<MyServerContext>().userName = name
  addTool(Server::greetUser) // Now, add greetUser
  return "Username set to: $name".toTextContent()
}

---

Resources

Resources are provided by a ResourceProvider. You can either create your own ResourceProvider or use one of the 2 default implementations:

DiscreteFileProvider

Let’s say you want to expose 2 files:

• /app/resources/cpp/my_program.h
• /app/resources/cpp/my_program.cpp

You would first create the following provider:

val fileProvider = DiscreteFileProvider(
  fileSystem = FileSystem.SYSTEM,
  rootDir = "/app/resources".toPath(),
  initialFiles = listOf(
    File(
      relativePath = "cpp/my_program.h",
      mimeType = "text/x-c++",
    ),
    File(
      relativePath = "cpp/my_program.cpp",
      mimeType = "text/x-c++",
    ),
  )
)

And add it when building the server:

val server = Server.Builder()
  .withResourceProvider(fileProvider)
  .withTransport(StdioTransport())
  .build()

A client calling resources/list will then receive:

{
  "resources": [
    {
      "uri": "file://cpp/my_program.h",
      "name": "my_program.h",
      "description": "File at cpp/my_program.h",
      "mimeType": "text/x-c++"
    },
    {
      "uri": "file://cpp/my_program.cpp",
      "name": "my_program.cpp",
      "description": "File at cpp/my_program.cpp",
      "mimeType": "text/x-c++"
    }
  ]
}

A client sending a resources/read request to fetch the contents of the source file would receive:

{
  "contents": [
    {
      "uri": "file://cpp/my_program.cpp",
      "mimeType": "text/x-c++",
      "text": "int main(){}"
    }
  ]
}

You can also add or remove files at runtime via

fileProvider.addFile(
  File(
    relativePath = "cpp/README.txt",
    mimeType = "text/plain",
  )
)

fileProvider.removeFile("cpp/my_program.h")

Both addFile and removeFile will send a notifications/resources/list_changed notification.

When making changes to a file, always call

fileProvider.onResourceChange("cpp/my_program.h")

If (and only if) the client subscribed to this resource, this will send a notifications/resources/updated notification to the client.

TemplateFileProvider

If you want to expose a whole directory, you can do:

val templateFileProvider = TemplateFileProvider(
  fileSystem = FileSystem.SYSTEM,
  rootDir = "/app/resources".toPath(),
)

A client calling resources/templates/list will receive:

{
  "resourceTemplates": [
    {
      "uriTemplate": "file:///{path}",
      "name": "Arbitrary local file access",
      "description": "Allows reading any file by specifying {path}"
    }
  ]
}

The client can then issue a resources/read request by providing the path:

{
  "method": "resources/read",
  "params": {
    "uri": "file:///cpp/my_program.cpp"
  }
}

This will read from /app/resources/cpp/my_program.cpp and return the result:

{
  "contents": [
    {
      "uri": "file:///cpp/my_program.cpp",
      "mimeType": "text/plain",
      "text": "int main(){}"
    }
  ]
}

Note the incorrect text/plain here - proper MIME detection will be added at some point.

Similarly to DiscreteFileProvider, when modifying a resource, call

templateFileProvider.onResourceChange("cpp/my_program.h")

to trigger the notification in case a client is subscribed to this resource.

Use those FileProviders only in a sand-boxed environment, they are NOT production-ready.

---

Sampling

Clients can fulfill server-initiated LLM requests by providing a SamplingProvider.

In a real application, you would call your favorite LLM API (e.g., OpenAI, Anthropic) inside the provider. Here’s a simplified example that always returns a dummy completion:

// 1) Define a sampling provider
val samplingProvider = SamplingProvider { params: CreateMessageParams ->
  CreateMessageResult(
    model = "dummy-model",
    role = Role.ASSISTANT,
    content = TextContent("Dummy completion result"),
    stopReason = "endTurn",
  )
}

// 2) Build the client with sampling support
val client = Client.Builder()
  .withTransport(StdioTransport())
  .withPermissionCallback { userApprovable -> 
    // Prompt the user for confirmation here
    true 
  }
  .withSamplingProvider(samplingProvider) // Register the provider
  .build()

runBlocking {
  client.start()
  client.initialize()

  // Now, if a server sends a "sampling/createMessage" request, 
  // the samplingProvider will be invoked to generate a response.
}

---

Request Cancellations

mcp4k uses Kotlin coroutines for cooperative cancellation. For example, a long-running server tool:

@McpTool
suspend fun slowToolOperation(iterations: Int = 10): ToolContent {
  for (i in 1..iterations) {
    delay(1000)
  }
  return "Operation completed after $iterations".toTextContent()
}

The client can cancel mid-operation:

val requestJob = launch {
  client.sendRequest { id ->
    CallToolRequest(
      id = id,
      params = CallToolRequest.CallToolParams(
        name = "slowToolOperation",
        arguments = mapOf("iterations" to 20),
      ),
    )
  }
}
delay(600)
requestJob.cancel("User doesn't want to wait anymore")

Under the hood, mcp4k sends a notification to the server:

{
  "method": "notifications/cancelled",
  "jsonrpc": "2.0",
  "params": {
    "requestId": "2",
    "reason": "Client doesn't want to wait anymore"
  }
}

and the server will abort the suspended tool operation.

---

Roadmap

✅ Add resource capability
✅ @McpTool and @McpPrompt functions
✅ Request cancellations
✅ Pagination
✅ Sampling (client-side)
✅ Roots
✅ Transport logging
✅ SourceSink Transport
✅ onToolsChanged callback in Client
⬜ Support other Kotlin versions
⬜ Completions
⬜ Support logging levels
⬜ Proper version negotiation
⬜ Emit progress notifications from @McpTool functions
⬜ Proper MIME detection
⬜ Add FileWatcher to automate resources/updated notifications
⬜ HTTP-Streaming transport
⬜ Add references, property descriptions and validation keywords to the JSON schemas

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How mcp4k Works

• Annotated @McpTool and @McpPrompt functions are processed at compile time.
• mcp4k generates JSON schemas, request handlers, and registration code automatically.
• Generated code is injected during Kotlin’s IR compilation phase, guaranteeing type-safe usage.
• If your KDoc references unknown parameters, the build fails, forcing you to keep docs in sync with code.

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Contributing

Issues and pull requests are welcome!
Feel free to open a discussion or contribute improvements.

License: mcp4k is available under the Apache License 2.0.