MCP Kotlin SDK

Kotlin Multiplatform SDK for the Model Context Protocol. It enables Kotlin applications targeting JVM, Native, JS, and Wasm to implement MCP clients and servers using a standardized protocol interface.

Table of Contents

• Overview
• Installation
  • Artifacts
  • Gradle setup (JVM)
  • Multiplatform
  • Ktor dependencies
• Quickstart
  • Creating a Client
  • Creating a Server
• Core Concepts
  • MCP Primitives
  • Capabilities
    • Server Capabilities
    • Client Capabilities
  • Server Features
    • Prompts
    • Resources
    • Tools
    • Completion
    • Logging
    • Pagination
  • Client Features
    • Roots
    • Sampling
• Transports
  • STDIO Transport
  • Streamable HTTP Transport
  • SSE Transport
  • WebSocket Transport
  • ChannelTransport (testing)
• Connecting your server
• Examples
• Documentation
• Contributing
• License

Overview

The Model Context Protocol allows applications to provide context for LLMs in a standardized way, separating the concerns of providing context from the actual LLM interaction. This Kotlin SDK implements the MCP specification, making it easy to:

• Build MCP clients that can connect to any MCP server
• Create MCP servers that expose resources, prompts, and tools
• Target JVM, Native, JS, and Wasm from a single codebase
• Use standard transports like stdio, SSE, Streamable HTTP, and WebSocket
• Handle MCP protocol messages and lifecycle events with coroutine-friendly APIs

Installation

Artifacts

• io.modelcontextprotocol:kotlin-sdk – umbrella SDK (client + server APIs)
• io.modelcontextprotocol:kotlin-sdk-client – client-only APIs
• io.modelcontextprotocol:kotlin-sdk-server – server-only APIs

Gradle setup (JVM)

Add the Maven Central repository and the SDK dependency:

repositories {
    mavenCentral()
}

dependencies {
    // See the badge above for the latest version
    implementation("io.modelcontextprotocol:kotlin-sdk:$mcpVersion")
}

Use kotlin-sdk-client or kotlin-sdk-server if you only need one side of the API:

dependencies {
    implementation("io.modelcontextprotocol:kotlin-sdk-client:$mcpVersion")
    implementation("io.modelcontextprotocol:kotlin-sdk-server:$mcpVersion")
}

Multiplatform

In a Kotlin Multiplatform project you can add the SDK to commonMain:

commonMain {
    dependencies {
        // Works as a common dependency as well as the platform one
        implementation("io.modelcontextprotocol:kotlin-sdk:$mcpVersion")
    }
}

Ktor dependencies

The Kotlin MCP SDK uses Ktor, but it does not add Ktor engine dependencies transitively. You need to declare Ktor client/server dependencies yourself (or reuse the ones already used in your project), for example:

dependencies {
    // MCP client with Ktor
    implementation("io.ktor:ktor-client-cio:$ktorVersion")
    implementation("io.modelcontextprotocol:kotlin-sdk-client:$mcpVersion")

    // MCP server with Ktor
    implementation("io.ktor:ktor-server-netty:$ktorVersion")
    implementation("io.modelcontextprotocol:kotlin-sdk-server:$mcpVersion")
}

Quickstart

Let's create a simple MCP client and server to demonstrate the basic usage of the Kotlin SDK.

Creating a Client

Create an MCP client that connects to a server via Streamable HTTP transport and lists available tools:

import io.ktor.client.HttpClient
import io.ktor.client.plugins.sse.SSE
import io.modelcontextprotocol.kotlin.sdk.client.Client
import io.modelcontextprotocol.kotlin.sdk.client.StreamableHttpClientTransport
import io.modelcontextprotocol.kotlin.sdk.types.Implementation
import kotlinx.coroutines.runBlocking

fun main(args: Array<String>) = runBlocking {
    val url = args.firstOrNull() ?: "http://localhost:3000/mcp"

    val httpClient = HttpClient { install(SSE) }

    val client = Client(
        clientInfo = Implementation(
            name = "example-client",
            version = "1.0.0"
        )
    )

    val transport = StreamableHttpClientTransport(
        client = httpClient,
        url = url
    )

    // Connect to server
    client.connect(transport)

    // List available tools
    val tools = client.listTools().tools

    println(tools)
}

Creating a Server

Create an MCP server that exposes a simple tool and runs on an embedded Ktor server with Streamable HTTP transport. For a full working project with all required dependencies, see the simple-streamable-server sample.

import io.ktor.server.cio.CIO
import io.ktor.server.engine.embeddedServer
import io.modelcontextprotocol.kotlin.sdk.server.Server
import io.modelcontextprotocol.kotlin.sdk.server.ServerOptions
import io.modelcontextprotocol.kotlin.sdk.server.mcpStreamableHttp
import io.modelcontextprotocol.kotlin.sdk.types.CallToolResult
import io.modelcontextprotocol.kotlin.sdk.types.Implementation
import io.modelcontextprotocol.kotlin.sdk.types.ServerCapabilities
import io.modelcontextprotocol.kotlin.sdk.types.TextContent
import io.modelcontextprotocol.kotlin.sdk.types.ToolSchema
import kotlinx.serialization.json.buildJsonObject
import kotlinx.serialization.json.put

fun main(args: Array<String>) {
    val port = args.firstOrNull()?.toIntOrNull() ?: 3000
    val mcpServer = Server(
        serverInfo = Implementation(
            name = "example-server",
            version = "1.0.0"
        ),
        options = ServerOptions(
            capabilities = ServerCapabilities(
                tools = ServerCapabilities.Tools(listChanged = true),
            ),
        )
    )

    mcpServer.addTool(
        name = "example-tool",
        description = "An example tool",
        inputSchema = ToolSchema(
            properties = buildJsonObject {
                put("input", buildJsonObject { put("type", "string") })
            }
        )
    ) { request ->
        CallToolResult(content = listOf(TextContent("Hello, world!")))
    }
    
    embeddedServer(CIO, host = "127.0.0.1", port = port) {
        mcpStreamableHttp {
            mcpServer
        }
    }.start(wait = true)
}

You can run the server and then connect to it using the client or test with the MCP Inspector:

npx -y @modelcontextprotocol/inspector

In the inspector UI, connect to http://localhost:3000/mcp.

Core Concepts

MCP Primitives

The MCP protocol defines core primitives that enable communication between servers and clients:

Primitive	Server Role	Client Role	Description
Prompts	Provides prompt templates with optional arguments	Requests and uses prompts	Interactive templates for LLM interactions
Resources	Exposes data sources (files, API responses, etc.)	Reads and subscribes to resources	Contextual data for augmenting LLM context
Tools	Defines executable functions	Calls tools to perform actions	Functions the LLM can invoke to take actions
Sampling	Requests LLM completions from client	Executes LLM calls and returns results	Server-initiated LLM requests (reverse direction)

Capabilities

Capabilities define what features a server or client supports. They are declared during initialization and determine what operations are available.

Server Capabilities

Servers declare their capabilities to inform clients what features they provide:

Capability	Feature Flags	Description
prompts	listChanged	Prompt template management and notifications
resources	subscribe listChanged	Resource exposure, subscriptions, and update notifications
tools	listChanged	Tool discovery, execution, and list change notifications
logging	-	Server logging to client console
completions	-	Argument autocompletion suggestions
experimental	Custom properties	Non-standard experimental features

Client Capabilities

Clients declare their capabilities to inform servers what features they support:

Capability	Feature Flags	Description
sampling	-	Client can sample from an LLM (execute model requests)
roots	listChanged	Client exposes root directories and can notify of changes
elicitation	-	Client can display schema/form dialogs for structured input
experimental	Custom properties	Non-standard experimental features

Server Features

The Server API lets you wire prompts, resources, and tools with only a few lines of Kotlin. Each feature is registered up front and then resolved lazily when a client asks for it, so your handlers stay small and suspendable.

Prompts

Prompts are user-controlled templates that clients discover via prompts/list and fetch with prompts/get when a user chooses one (think slash commands or saved flows). They’re best for repeatable, structured starters rather than ad-hoc model calls.

val server = Server(
    serverInfo = Implementation(
        name = "example-server",
        version = "1.0.0"
    ),
    options = ServerOptions(
        capabilities = ServerCapabilities(
            prompts = ServerCapabilities.Prompts(listChanged = true),
        ),
    )
)

server.addPrompt(
    name = "code-review",
    description = "Ask the model to review a diff",
    arguments = listOf(
        PromptArgument(name = "diff", description = "Unified diff", required = true),
    ),
) { request ->
    GetPromptResult(
        description = "Quick code review helper",
        messages = listOf(
            PromptMessage(
                role = Role.User,
                content = TextContent(text = "Review this change:\n${request.arguments?.get("diff")}"),
            ),
        ),
    )
}

Use prompts for anything that deserves a template: bug triage questions, onboarding checklists, or saved searches. Set listChanged = true only if your prompt catalog can change at runtime and your server will emit notifications/prompts/list_changed when it does.

Resources

Resources are application-driven context that clients discover via resources/list or resources/templates/list, then fetch with resources/read. Register each one with a stable URI and return a ReadResourceResult when asked—contents can be text or binary blobs.

val server = Server(
    serverInfo = Implementation(
        name = "example-server",
        version = "1.0.0"
    ),
    options = ServerOptions(
        capabilities = ServerCapabilities(
            resources = ServerCapabilities.Resources(subscribe = true, listChanged = true),
        ),
    )
)

server.addResource(
    uri = "note://release/latest",
    name = "Release notes",
    description = "Last deployment summary",
    mimeType = "text/markdown",
) { request ->
    ReadResourceResult(
        contents = listOf(
            TextResourceContents(
                text = "Ship 42 reached production successfully.",
                uri = request.uri,
                mimeType = "text/markdown",
            ),
        ),
    )
}

Resources can be static text, generated JSON, or blobs—anything the client can surface to the user or inject into the model context. Set subscribe = true if you emit notifications/resources/updated for changes to specific URIs, and listChanged = true if you’ll send notifications/resources/list_changed when the catalog itself changes.

Tools

Tools are model-controlled capabilities the client exposes to the model. Clients discover them via tools/list, invoke them with tools/call, and your handlers receive JSON arguments, can emit streaming logs or progress, and return a CallToolResult. Keep a human in the loop for sensitive operations.

val server = Server(
    serverInfo = Implementation(
        name = "example-server",
        version = "1.0.0"
    ),
    options = ServerOptions(
        capabilities = ServerCapabilities(
            tools = ServerCapabilities.Tools(listChanged = true),
        ),
    )
)

server.addTool(
    name = "echo",
    description = "Return whatever the user sent back to them",
) { request ->
    val text = request.arguments?.get("text")?.jsonPrimitive?.content ?: "(empty)"
    CallToolResult(content = listOf(TextContent(text = "Echo: $text")))
}

Register as many tools as you need—long-running jobs can report progress via the request context, and tools can also trigger sampling (see below) when they need the client’s LLM. Set listChanged = true only if your tool catalog can change at runtime and your server will emit notifications/tools/list_changed when it does.

Completion

Completion provides argument suggestions for prompts or resource templates. Declare the completions capability and handle completion/complete requests to return up to 100 ranked values (include total/hasMore if you paginate).

val server = Server(
    serverInfo = Implementation(
        name = "example-server",
        version = "1.0.0"
    ),
    options = ServerOptions(
        capabilities = ServerCapabilities(
            completions = ServerCapabilities.Completions,
        ),
    )
)

val session = server.createSession(
    StdioServerTransport(
        inputStream = System.`in`.asSource().buffered(),
        outputStream = System.out.asSink().buffered()
    )
)

session.setRequestHandler<CompleteRequest>(Method.Defined.CompletionComplete) { request, _ ->
    val options = listOf("kotlin", "compose", "coroutine")
    val matches = options.filter { it.startsWith(request.argument.value.lowercase()) }

    CompleteResult(
        completion = CompleteResult.Completion(
            values = matches.take(3),
            total = matches.size,
            hasMore = matches.size > 3,
        ),
    )
}

Use context.arguments to refine suggestions for dependent fields (e.g., framework list filtered by chosen language).

Logging

Logging lets the server stream structured log notifications to the client using RFC 5424 levels (debug → emergency). Declare the logging capability; clients can raise the minimum level with logging/setLevel, and the server emits notifications/message with severity, optional logger name, and JSON data.

val server = Server(
    serverInfo = Implementation("example-server", "1.0.0"),
    options = ServerOptions(
        capabilities = ServerCapabilities(
            logging = ServerCapabilities.Logging,
        ),
    )
)

val session = server.createSession(
    StdioServerTransport(
        inputStream = System.`in`.asSource().buffered(),
        outputStream = System.out.asSink().buffered()
    )
)

session.sendLoggingMessage(
    LoggingMessageNotification(
        LoggingMessageNotificationParams(
            level = LoggingLevel.Info,
            logger = "startup",
            data = buildJsonObject { put("message", "Server started") },
        ),
    ),
)

Keep logs free of sensitive data, and expect clients to surface them in their own UI.

Pagination

List operations return paginated results with an opaque nextCursor, clients echo that cursor to fetch the next page. Supported list calls: resources/list, resources/templates/list, prompts/list, and tools/list. Treat cursors as opaque—don’t parse or persist them across sessions.

val server = Server(
    serverInfo = Implementation("example-server", "1.0.0"),
    options = ServerOptions(
        capabilities = ServerCapabilities(
            resources = ServerCapabilities.Resources(),
        ),
    )
)

val session = server.createSession(
    StdioServerTransport(
        inputStream = System.`in`.asSource().buffered(),
        outputStream = System.out.asSink().buffered()
    )
)

val resources = listOf(
    Resource(uri = "note://1", name = "Note 1", description = "First"),
    Resource(uri = "note://2", name = "Note 2", description = "Second"),
    Resource(uri = "note://3", name = "Note 3", description = "Third"),
)
val pageSize = 2

session.setRequestHandler<ListResourcesRequest>(Method.Defined.ResourcesList) { request, _ ->
    val start = request.params?.cursor?.toIntOrNull() ?: 0
    val page = resources.drop(start).take(pageSize)
    val next = if (start + page.size < resources.size) (start + page.size).toString() else null

    ListResourcesResult(
        resources = page,
        nextCursor = next,
    )
}

Include nextCursor only when more items remain an absent cursor ends pagination.

Client Features

Clients advertise their capabilities (roots, sampling, elicitation, etc.) during initialization. After that they can serve requests from the server while still initiating calls such as listTools or callTool.

Roots

Roots let the client declare where the server is allowed to operate. Declare the roots capability, respond to roots/list, and emit notifications/roots/list_changed if you set listChanged = true. URIs must be file:// paths.

val client = Client(
    clientInfo = Implementation("demo-client", "1.0.0"),
    options = ClientOptions(
        capabilities = ClientCapabilities(roots = ClientCapabilities.Roots(listChanged = true)),
    ),
)

client.addRoot(
    uri = "file:///Users/demo/projects",
    name = "Projects",
)
client.sendRootsListChanged()

Call addRoot/removeRoot whenever your file system view changes, and use sendRootsListChanged() to notify the server. Keep root lists user-controlled and revoke entries that are no longer authorized.

Sampling

Sampling lets the server ask the client to call its preferred LLM. Declare the sampling capability (and sampling.tools if you allow tool-enabled sampling), and handle sampling/createMessage. Keep a human in the loop for approvals.

val client = Client(
    clientInfo = Implementation("demo-client", "1.0.0"),
    options = ClientOptions(
        capabilities = ClientCapabilities(
            sampling = buildJsonObject { putJsonObject("tools") { } }, // drop tools if you don't support tool use
        ),
    ),
)

client.setRequestHandler<CreateMessageRequest>(Method.Defined.SamplingCreateMessage) { request, _ ->
    val content = request.messages.lastOrNull()?.content?.firstOrNull()
    val prompt = if (content is TextContent) content.text else "your topic"
    CreateMessageResult(
        model = "gpt-4o-mini",
        role = Role.Assistant,
        content = TextContent(text = "Here is a short note about $prompt"),
    )
}

Inside the handler you can pick any model/provider, require approvals, or reject the request. If you don’t support tool use, omit sampling.tools from capabilities.

Transports

All transports share the same API surface, so you can change deployment style without touching business logic. Pick the transport that best matches where the server runs.

STDIO Transport

StdioClientTransport and StdioServerTransport tunnel MCP messages over stdin/stdout—perfect for editor plugins or CLI tooling that spawns a helper process. No networking setup is required.

Streamable HTTP Transport

StreamableHttpClientTransport and the Ktor mcpStreamableHttp() / mcpStatelessStreamableHttp() helpers expose MCP over a single HTTP endpoint with optional JSON-only or SSE streaming responses. This is the recommended choice for remote deployments and integrates nicely with proxies or service meshes.

These helpers automatically install ContentNegotiation with McpJson — do not install it yourself, or a warning will be logged. Both accept a path parameter (default: "/mcp") to mount the endpoint at any URL:

embeddedServer(CIO, port = 3000) {
    mcpStreamableHttp(path = "/api/mcp") {
        MyServer()
    }
}.start(wait = true)

CORS for browser-based clients (e.g. MCP Inspector): if you connect from a browser-based client you need to install the Ktor CORS plugin so that MCP-specific headers are allowed and exposed:

install(CORS) {
    anyHost() // restrict to specific origins in production
    allowMethod(HttpMethod.Options)
    allowMethod(HttpMethod.Get)
    allowMethod(HttpMethod.Post)
    allowMethod(HttpMethod.Delete)
    allowNonSimpleContentTypes = true
    allowHeader("Mcp-Session-Id")
    allowHeader("Mcp-Protocol-Version")
    exposeHeader("Mcp-Session-Id")
    exposeHeader("Mcp-Protocol-Version")
}

SSE Transport

Server-Sent Events remain available for backwards compatibility with older MCP clients. Two Ktor helpers are provided:

• Application.mcp { } — installs SSE and ContentNegotiation with McpJson automatically, then registers MCP endpoints at /. Do not install ContentNegotiation yourself — the SDK handles it.
• Route.mcp { } — registers MCP endpoints at the current route path; requires install(SSE) in the application first. Use this to host MCP alongside other routes or under a path prefix:

embeddedServer(CIO, port = 3000) {
    install(SSE)
    routing {
        route("/api/mcp") {
            mcp { MyServer() }
        }
    }
}.start(wait = true)

Prefer Streamable HTTP for new projects.

WebSocket Transport

WebSocketClientTransport plus the matching server utilities provide full-duplex, low-latency connections—useful when you expect lots of notifications or long-running sessions behind a reverse proxy that already terminates WebSockets.

ChannelTransport (testing)

ChannelTransport provides a simple, non-networked transport for testing and local development. It uses Kotlin coroutines channels to provide a full-duplex connection between a client and server, allowing for easy testing of MCP functionality without the need for network setup.

Connecting your server

1. Start a sample HTTP server on port 3000:

   ./gradlew :samples:kotlin-mcp-server:run
   

2. Connect with the MCP Inspector or Claude Desktop/Code:

   npx -y @modelcontextprotocol/inspector --connect http://localhost:3000
   # or
   claude mcp add --transport http kotlin-mcp http://localhost:3000
   

3. In the Inspector, confirm prompts, tools, resources, completions, and logs show up. Iterate locally until you’re ready to host the server wherever you prefer.

Examples

The samples directory contains runnable projects demonstrating MCP server and client implementations with various transports. See the samples overview for a comparison table and detailed descriptions.

Documentation

• API Reference
• Model Context Protocol documentation
• MCP specification

Contributing

Please see the contribution guide and the Code of conduct before contributing.

License

This project is licensed under Apache 2.0 for new contributions, with existing code under MIT—see the LICENSE file for details.