FastMCP

A TypeScript framework for building MCP servers capable of handling client sessions.

Note

For a Python implementation, see FastMCP.

Features

Simple Tool, Resource, Prompt definition
Authentication
Passing headers through context
Session ID and Request ID tracking
Sessions
Image content
Audio content
Embedded
Logging
Error handling
HTTP Streaming (with SSE compatibility)
Stateless mode for serverless deployments
CORS (enabled by default)
Progress notifications
Streaming output
Typed server events
Prompt argument auto-completion
Sampling
Configurable ping behavior
Health-check endpoint
Roots
CLI for testing and debugging

When to use FastMCP over the official SDK?

FastMCP is built on top of the official SDK.

The official SDK provides foundational blocks for building MCPs, but leaves many implementation details to you:

Initiating and configuring all the server components
Handling of connections
Handling of tools
Handling of responses
Handling of resources
Adding prompts, resources, resource templates
Embedding resources, image and audio content blocks

FastMCP eliminates this complexity by providing an opinionated framework that:

Handles all the boilerplate automatically
Provides simple, intuitive APIs for common tasks
Includes built-in best practices and error handling
Lets you focus on your MCP's core functionality

When to choose FastMCP: You want to build MCP servers quickly without dealing with low-level implementation details.

When to use the official SDK: You need maximum control or have specific architectural requirements. In this case, we encourage referencing FastMCP's implementation to avoid common pitfalls.

Installation

npm install fastmcp

Quickstart

Note

There are many real-world examples of using FastMCP in the wild. See the Showcase for examples.

import { FastMCP } from "fastmcp";
import { z } from "zod"; // Or any validation library that supports Standard Schema

const server = new FastMCP({
  name: "My Server",
  version: "1.0.0",
});

server.addTool({
  name: "add",
  description: "Add two numbers",
  parameters: z.object({
    a: z.number(),
    b: z.number(),
  }),
  execute: async (args) => {
    return String(args.a + args.b);
  },
});

server.start({
  transportType: "stdio",
});

That's it! You have a working MCP server.

You can test the server in terminal with:

git clone https://github.com/punkpeye/fastmcp.git
cd fastmcp

pnpm install
pnpm build

# Test the addition server example using CLI:
npx fastmcp dev src/examples/addition.ts
# Test the addition server example using MCP Inspector:
npx fastmcp inspect src/examples/addition.ts

If you are looking for a boilerplate repository to build your own MCP server, check out fastmcp-boilerplate.

Remote Server Options

FastMCP supports multiple transport options for remote communication, allowing an MCP hosted on a remote machine to be accessed over the network.

HTTP Streaming

HTTP streaming provides a more efficient alternative to SSE in environments that support it, with potentially better performance for larger payloads.

You can run the server with HTTP streaming support:

server.start({
  transportType: "httpStream",
  httpStream: {
    port: 8080,
  },
});

This will start the server and listen for HTTP streaming connections on http://localhost:8080/mcp.

Note: You can also customize the endpoint path using the httpStream.endpoint option (default is /mcp).

Note: This also starts an SSE server on http://localhost:8080/sse.

You can connect to these servers using the appropriate client transport.

For HTTP streaming connections:

import { StreamableHTTPClientTransport } from "@modelcontextprotocol/sdk/client/streamableHttp.js";

const client = new Client(
  {
    name: "example-client",
    version: "1.0.0",
  },
  {
    capabilities: {},
  },
);

const transport = new StreamableHTTPClientTransport(
  new URL(`http://localhost:8080/mcp`),
);

await client.connect(transport);

For SSE connections:

import { SSEClientTransport } from "@modelcontextprotocol/sdk/client/sse.js";

const client = new Client(
  {
    name: "example-client",
    version: "1.0.0",
  },
  {
    capabilities: {},
  },
);

const transport = new SSEClientTransport(new URL(`http://localhost:8080/sse`));

await client.connect(transport);

Stateless Mode

FastMCP supports stateless operation for HTTP streaming, where each request is handled independently without maintaining persistent sessions. This is ideal for serverless environments, load-balanced deployments, or when session state isn't required.

In stateless mode:

No sessions are tracked on the server
Each request creates a temporary session that's discarded after the response
Reduced memory usage and better scalability
Perfect for stateless deployment environments

You can enable stateless mode by adding the stateless: true option:

server.start({
  transportType: "httpStream",
  httpStream: {
    port: 8080,
    stateless: true,
  },
});

Note: Stateless mode is only available with HTTP streaming transport. Features that depend on persistent sessions (like session-specific state) will not be available in stateless mode.

You can also enable stateless mode using CLI arguments or environment variables:

# Via CLI argument
npx fastmcp dev src/server.ts --transport http-stream --port 8080 --stateless true

# Via environment variable
FASTMCP_STATELESS=true npx fastmcp dev src/server.ts

The /ready health check endpoint will indicate when the server is running in stateless mode:

{
  "mode": "stateless",
  "ready": 1,
  "status": "ready",
  "total": 1
}

Core Concepts

Tools

Tools in MCP allow servers to expose executable functions that can be invoked by clients and used by LLMs to perform actions.

FastMCP uses the Standard Schema specification for defining tool parameters. This allows you to use your preferred schema validation library (like Zod, ArkType, or Valibot) as long as it implements the spec.

Zod Example:

import { z } from "zod";

server.addTool({
  name: "fetch-zod",
  description: "Fetch the content of a url (using Zod)",
  parameters: z.object({
    url: z.string(),
  }),
  execute: async (args) => {
    return await fetchWebpageContent(args.url);
  },
});

ArkType Example:

import { type } from "arktype";

server.addTool({
  name: "fetch-arktype",
  description: "Fetch the content of a url (using ArkType)",
  parameters: type({
    url: "string",
  }),
  execute: async (args) => {
    return await fetchWebpageContent(args.url);
  },
});

Valibot Example:

Valibot requires the peer dependency @valibot/to-json-schema.

import * as v from "valibot";

server.addTool({
  name: "fetch-valibot",
  description: "Fetch the content of a url (using Valibot)",
  parameters: v.object({
    url: v.string(),
  }),
  execute: async (args) => {
    return await fetchWebpageContent(args.url);
  },
});

Tools Without Parameters

When creating tools that don't require parameters, you have two options:

Omit the parameters property entirely:

server.addTool({
  name: "sayHello",
  description: "Say hello",
  // No parameters property
  execute: async () => {
    return "Hello, world!";
  },
});

Explicitly define empty parameters:

import { z } from "zod";

server.addTool({
  name: "sayHello",
  description: "Say hello",
  parameters: z.object({}), // Empty object
  execute: async () => {
    return "Hello, world!";
  },
});

Note

Both approaches are fully compatible with all MCP clients, including Cursor. FastMCP automatically generates the proper schema in both cases.

Tool Authorization

You can control which tools are available to authenticated users by adding an optional canAccess function to a tool's definition. This function receives the authentication context and should return true if the user is allowed to access the tool.

server.addTool({
  name: "admin-tool",
  description: "An admin-only tool",
  canAccess: (auth) => auth?.role === "admin",
  execute: async () => "Welcome, admin!",
});

Returning a string

execute can return a string:

server.addTool({
  name: "download",
  description: "Download a file",
  parameters: z.object({
    url: z.string(),
  }),
  execute: async (args) => {
    return "Hello, world!";
  },
});

The latter is equivalent to:

server.addTool({
  name: "download",
  description: "Download a file",
  parameters: z.object({
    url: z.string(),
  }),
  execute: async (args) => {
    return {
      content: [
        {
          type: "text",
          text: "Hello, world!",
        },
      ],
    };
  },
});

Returning a list

If you want to return a list of messages, you can return an object with a content property:

server.addTool({
  name: "download",
  description: "Download a file",
  parameters: z.object({
    url: z.string(),
  }),
  execute: async (args) => {
    return {
      content: [
        { type: "text", text: "First message" },
        { type: "text", text: "Second message" },
      ],
    };
  },
});

Returning an image

Use the imageContent to create a content object for an image:

import { imageContent } from "fastmcp";

server.addTool({
  name: "download",
  description: "Download a file",
  parameters: z.object({
    url: z.string(),
  }),
  execute: async (args) => {
    return imageContent({
      url: "https://example.com/image.png",
    });

    // or...
    // return imageContent({
    //   path: "/path/to/image.png",
    // });

    // or...
    // return imageContent({
    //   buffer: Buffer.from("iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mNkYAAAAAYAAjCB0C8AAAAASUVORK5CYII=", "base64"),
    // });

    // or...
    // return {
    //   content: [
    //     await imageContent(...)
    //   ],
    // };
  },
});

The imageContent function takes the following options:

url: The URL of the image.
path: The path to the image file.
buffer: The image data as a buffer.

Only one of url, path, or buffer must be specified.

The above example is equivalent to:

server.addTool({
  name: "download",
  description: "Download a file",
  parameters: z.object({
    url: z.string(),
  }),
  execute: async (args) => {
    return {
      content: [
        {
          type: "image",
          data: "iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mNkYAAAAAYAAjCB0C8AAAAASUVORK5CYII=",
          mimeType: "image/png",
        },
      ],
    };
  },
});

Configurable Ping Behavior

FastMCP includes a configurable ping mechanism to maintain connection health. The ping behavior can be customized through server options:

const server = new FastMCP({
  name: "My Server",
  version: "1.0.0",
  ping: {
    // Explicitly enable or disable pings (defaults vary by transport)
    enabled: true,
    // Configure ping interval in milliseconds (default: 5000ms)
    intervalMs: 10000,
    // Set log level for ping-related messages (default: 'debug')
    logLevel: "debug",
  },
});

By default, ping behavior is optimized for each transport type:

Enabled for SSE and HTTP streaming connections (which benefit from keep-alive)
Disabled for stdio connections (where pings are typically unnecessary)

This configurable approach helps reduce log verbosity and optimize performance for different usage scenarios.

Health-check Endpoint

When you run FastMCP with the httpStream transport you can optionally expose a simple HTTP endpoint that returns a plain-text response useful for load-balancer or container orchestration liveness checks.

Enable (or customise) the endpoint via the health key in the server options:

const server = new FastMCP({
  name: "My Server",
  version: "1.0.0",
  health: {
    // Enable / disable (default: true)
    enabled: true,
    // Body returned by the endpoint (default: 'ok')
    message: "healthy",
    // Path that should respond (default: '/health')
    path: "/healthz",
    // HTTP status code to return (default: 200)
    status: 200,
  },
});

await server.start({
  transportType: "httpStream",
  httpStream: { port: 8080 },
});

Now a request to http://localhost:8080/healthz will return:

HTTP/1.1 200 OK
content-type: text/plain

healthy

The endpoint is ignored when the server is started with the stdio transport.

Roots Management

FastMCP supports Roots - Feature that allows clients to provide a set of filesystem-like root locations that can be listed and dynamically updated. The Roots feature can be configured or disabled in server options:

const server = new FastMCP({
  name: "My Server",
  version: "1.0.0",
  roots: {
    // Set to false to explicitly disable roots support
    enabled: false,
    // By default, roots support is enabled (true)
  },
});

This provides the following benefits:

Better compatibility with different clients that may not support Roots
Reduced error logs when connecting to clients that don't implement roots capability
More explicit control over MCP server capabilities
Graceful degradation when roots functionality isn't available

You can listen for root changes in your server:

server.on("connect", (event) => {
  const session = event.session;

  // Access the current roots
  console.log("Initial roots:", session.roots);

  // Listen for changes to the roots
  session.on("rootsChanged", (event) => {
    console.log("Roots changed:", event.roots);
  });
});

When a client doesn't support roots or when roots functionality is explicitly disabled, these operations will gracefully handle the situation without throwing errors.

Returning an audio

Use the audioContent to create a content object for an audio:

import { audioContent } from "fastmcp";

server.addTool({
  name: "download",
  description: "Download a file",
  parameters: z.object({
    url: z.string(),
  }),
  execute: async (args) => {
    return audioContent({
      url: "https://example.com/audio.mp3",
    });

    // or...
    // return audioContent({
    //   path: "/path/to/audio.mp3",
    // });

    // or...
    // return audioContent({
    //   buffer: Buffer.from("iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mNkYAAAAAYAAjCB0C8AAAAASUVORK5CYII=", "base64"),
    // });

    // or...
    // return {
    //   content: [
    //     await audioContent(...)
    //   ],
    // };
  },
});

The audioContent function takes the following options:

url: The URL of the audio.
path: The path to the audio file.
buffer: The audio data as a buffer.

Only one of url, path, or buffer must be specified.

The above example is equivalent to:

server.addTool({
  name: "download",
  description: "Download a file",
  parameters: z.object({
    url: z.string(),
  }),
  execute: async (args) => {
    return {
      content: [
        {
          type: "audio",
          data: "iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mNkYAAAAAYAAjCB0C8AAAAASUVORK5CYII=",
          mimeType: "audio/mpeg",
        },
      ],
    };
  },
});

Return combination type

You can combine various types in this way and send them back to AI

server.addTool({
  name: "download",
  description: "Download a file",
  parameters: z.object({
    url: z.string(),
  }),
  execute: async (args) => {
    return {
      content: [
        {
          type: "text",
          text: "Hello, world!",
        },
        {
          type: "image",
          data: "iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mNkYAAAAAYAAjCB0C8AAAAASUVORK5CYII=",
          mimeType: "image/png",
        },
        {
          type: "audio",
          data: "iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mNkYAAAAAYAAjCB0C8AAAAASUVORK5CYII=",
          mimeType: "audio/mpeg",
        },
      ],
    };
  },

  // or...
  // execute: async (args) => {
  //   const imgContent = await imageContent({
  //     url: "https://example.com/image.png",
  //   });
  //   const audContent = await audioContent({
  //     url: "https://example.com/audio.mp3",
  //   });
  //   return {
  //     content: [
  //       {
  //         type: "text",
  //         text: "Hello, world!",
  //       },
  //       imgContent,
  //       audContent,
  //     ],
  //   };
  // },
});

Custom Logger

FastMCP allows you to provide a custom logger implementation to control how the server logs messages. This is useful for integrating with existing logging infrastructure or customizing log formatting.

import { FastMCP, Logger } from "fastmcp";

class CustomLogger implements Logger {
  debug(...args: unknown[]): void {
    console.log("[DEBUG]", new Date().toISOString(), ...args);
  }

  error(...args: unknown[]): void {
    console.error("[ERROR]", new Date().toISOString(), ...args);
  }

  info(...args: unknown[]): void {
    console.info("[INFO]", new Date().toISOString(), ...args);
  }

  log(...args: unknown[]): void {
    console.log("[LOG]", new Date().toISOString(), ...args);
  }

  warn(...args: unknown[]): void {
    console.warn("[WARN]", new Date().toISOString(), ...args);
  }
}

const server = new FastMCP({
  name: "My Server",
  version: "1.0.0",
  logger: new CustomLogger(),
});

See src/examples/custom-logger.ts for examples with Winston, Pino, and file-based logging.

Logging

Tools can log messages to the client using the log object in the context object:

server.addTool({
  name: "download",
  description: "Download a file",
  parameters: z.object({
    url: z.string(),
  }),
  execute: async (args, { log }) => {
    log.info("Downloading file...", {
      url,
    });

    // ...

    log.info("Downloaded file");

    return "done";
  },
});

The log object has the following methods:

debug(message: string, data?: SerializableValue)
error(message: string, data?: SerializableValue)
info(message: string, data?: SerializableValue)
warn(message: string, data?: SerializableValue)

Errors

The errors that are meant to be shown to the user should be thrown as UserError instances:

import { UserError } from "fastmcp";

server.addTool({
  name: "download",
  description: "Download a file",
  parameters: z.object({
    url: z.string(),
  }),
  execute: async (args) => {
    if (args.url.startsWith("https://example.com")) {
      throw new UserError("This URL is not allowed");
    }

    return "done";
  },
});

Progress

Tools can report progress by calling reportProgress in the context object:

server.addTool({
  name: "download",
  description: "Download a file",
  parameters: z.object({
    url: z.string(),
  }),
  execute: async (args, { reportProgress }) => {
    await reportProgress({
      progress: 0,
      total: 100,
    });

    // ...

    await reportProgress({
      progress: 100,
      total: 100,
    });

    return "done";
  },
});

Streaming Output

FastMCP supports streaming partial results from tools while they're still executing, enabling responsive UIs and real-time feedback. This is particularly useful for:

Long-running operations that generate content incrementally
Progressive generation of text, images, or other media
Operations where users benefit from seeing immediate partial results

To enable streaming for a tool, add the streamingHint annotation and use the streamContent method:

server.addTool({
  name: "generateText",
  description: "Generate text incrementally",
  parameters: z.object({
    prompt: z.string(),
  }),
  annotations: {
    streamingHint: true, // Signals this tool uses streaming
    readOnlyHint: true,
  },
  execute: async (args, { streamContent }) => {
    // Send initial content immediately
    await streamContent({ type: "text", text: "Starting generation...\n" });

    // Simulate incremental content generation
    const words = "The quick brown fox jumps over the lazy dog.".split(" ");
    for (const word of words) {
      await streamContent({ type: "text", text: word + " " });
      await new Promise((resolve) => setTimeout(resolve, 300)); // Simulate delay
    }

    // When using streamContent, you can:
    // 1. Return void (if all content was streamed)
    // 2. Return a final result (which will be appended to streamed content)

    // Option 1: All content was streamed, so return void
    return;

    // Option 2: Return final content that will be appended
    // return "Generation complete!";
  },
});

Streaming works with all content types (text, image, audio) and can be combined with progress reporting:

server.addTool({
  name: "processData",
  description: "Process data with streaming updates",
  parameters: z.object({
    datasetSize: z.number(),
  }),
  annotations: {
    streamingHint: true,
  },
  execute: async (args, { streamContent, reportProgress }) => {
    const total = args.datasetSize;

    for (let i = 0; i < total; i++) {
      // Report numeric progress
      await reportProgress({ progress: i, total });

      // Stream intermediate results
      if (i % 10 === 0) {
        await streamContent({
          type: "text",
          text: `Processed ${i} of ${total} items...\n`,
        });
      }

      await new Promise((resolve) => setTimeout(resolve, 50));
    }

    return "Processing complete!";
  },
});

Tool Annotations

As of the MCP Specification (2025-03-26), tools can include annotations that provide richer context and control by adding metadata about a tool's behavior:

server.addTool({
  name: "fetch-content",
  description: "Fetch content from a URL",
  parameters: z.object({
    url: z.string(),
  }),
  annotations: {
    title: "Web Content Fetcher", // Human-readable title for UI display
    readOnlyHint: true, // Tool doesn't modify its environment
    openWorldHint: true, // Tool interacts with external entities
  },
  execute: async (args) => {
    return await fetchWebpageContent(args.url);
  },
});

The available annotations are:

Annotation	Type	Default	Description
`title`	string	-	A human-readable title for the tool, useful for UI display
`readOnlyHint`	boolean	`false`	If true, indicates the tool does not modify its environment
`destructiveHint`	boolean	`true`	If true, the tool may perform destructive updates (only meaningful when `readOnlyHint` is false)
`idempotentHint`	boolean	`false`	If true, calling the tool repeatedly with the same arguments has no additional effect (only meaningful when `readOnlyHint` is false)
`openWorldHint`	boolean	`true`	If true, the tool may interact with an "open world" of external entities

These annotations help clients and LLMs better understand how to use the tools and what to expect when calling them.

Resources

Resources represent any kind of data that an MCP server wants to make available to clients. This can include:

File contents
Screenshots and images
Log files
And more

Each resource is identified by a unique URI and can contain either text or binary data.

server.addResource({
  uri: "file:///logs/app.log",
  name: "Application Logs",
  mimeType: "text/plain",
  async load() {
    return {
      text: await readLogFile(),
    };
  },
});

Note

load can return multiple resources. This could be used, for example, to return a list of files inside a directory when the directory is read.

async load() {
  return [
    {
      text: "First file content",
    },
    {
      text: "Second file content",
    },
  ];
}

You can also return binary contents in load:

async load() {
  return {
    blob: 'base64-encoded-data'
  };
}

Resource templates

You can also define resource templates:

server.addResourceTemplate({
  uriTemplate: "file:///logs/{name}.log",
  name: "Application Logs",
  mimeType: "text/plain",
  arguments: [
    {
      name: "name",
      description: "Name of the log",
      required: true,
    },
  ],
  async load({ name }) {
    return {
      text: `Example log content for ${name}`,
    };
  },
});

Resource template argument auto-completion

Provide complete functions for resource template arguments to enable automatic completion:

server.addResourceTemplate({
  uriTemplate: "file:///logs/{name}.log",
  name: "Application Logs",
  mimeType: "text/plain",
  arguments: [
    {
      name: "name",
      description: "Name of the log",
      required: true,
      complete: async (value) => {
        if (value === "Example") {
          return {
            values: ["Example Log"],
          };
        }

        return {
          values: [],
        };
      },
    },
  ],
  async load({ name }) {
    return {
      text: `Example log content for ${name}`,
    };
  },
});

Embedded Resources

FastMCP provides a convenient embedded() method that simplifies including resources in tool responses. This feature reduces code duplication and makes it easier to reference resources from within tools.

Basic Usage

server.addTool({
  name: "get_user_data",
  description: "Retrieve user information",
  parameters: z.object({
    userId: z.string(),
  }),
  execute: async (args) => {
    return {
      content: [
        {
          type: "resource",
          resource: await server.embedded(`user://profile/${args.userId}`),
        },
      ],
    };
  },
});

Working with Resource Templates

The embedded() method works seamlessly with resource templates:

// Define a resource template
server.addResourceTemplate({
  uriTemplate: "docs://project/{section}",
  name: "Project Documentation",
  mimeType: "text/markdown",
  arguments: [
    {
      name: "section",
      required: true,
    },
  ],
  async load(args) {
    const docs = {
      "getting-started": "# Getting Started\n\nWelcome to our project!",
      "api-reference": "# API Reference\n\nAuthentication is required.",
    };
    return {
      text: docs[args.section] || "Documentation not found",
    };
  },
});

// Use embedded resources in a tool
server.addTool({
  name: "get_documentation",
  description: "Retrieve project documentation",
  parameters: z.object({
    section: z.enum(["getting-started", "api-reference"]),
  }),
  execute: async (args) => {
    return {
      content: [
        {
          type: "resource",
          resource: await server.embedded(`docs://project/${args.section}`),
        },
      ],
    };
  },
});

Working with Direct Resources

It also works with directly defined resources:

// Define a direct resource
server.addResource({
  uri: "system://status",
  name: "System Status",
  mimeType: "text/plain",
  async load() {
    return {
      text: "System operational",
    };
  },
});

// Use in a tool
server.addTool({
  name: "get_system_status",
  description: "Get current system status",
  parameters: z.object({}),
  execute: async () => {
    return {
      content: [
        {
          type: "resource",
          resource: await server.embedded("system://status"),
        },
      ],
    };
  },
});

Prompts

Prompts enable servers to define reusable prompt templates and workflows that clients can easily surface to users and LLMs. They provide a powerful way to standardize and share common LLM interactions.

server.addPrompt({
  name: "git-commit",
  description: "Generate a Git commit message",
  arguments: [
    {
      name: "changes",
      description: "Git diff or description of changes",
      required: true,
    },
  ],
  load: async (args) => {
    return `Generate a concise but descriptive commit message for these changes:\n\n${args.changes}`;
  },
});

Prompt argument auto-completion

Prompts can provide auto-completion for their arguments:

server.addPrompt({
  name: "countryPoem",
  description: "Writes a poem about a country",
  load: async ({ name }) => {
    return `Hello, ${name}!`;
  },
  arguments: [
    {
      name: "name",
      description: "Name of the country",
      required: true,
      complete: async (value) => {
        if (value === "Germ") {
          return {
            values: ["Germany"],
          };
        }

        return {
          values: [],
        };
      },
    },
  ],
});

Prompt argument auto-completion using `enum`

If you provide an enum array for an argument, the server will automatically provide completions for the argument.

server.addPrompt({
  name: "countryPoem",
  description: "Writes a poem about a country",
  load: async ({ name }) => {
    return `Hello, ${name}!`;
  },
  arguments: [
    {
      name: "name",
      description: "Name of the country",
      required: true,
      enum: ["Germany", "France", "Italy"],
    },
  ],
});

Authentication

FastMCP supports session-based authentication, allowing you to secure your server and control access to its features.

Note

For more granular control over which tools are available to authenticated users, see the Tool Authorization section.

To enable authentication, provide an authenticate function in the server options. This function receives the incoming HTTP request and should return a promise that resolves with the authentication context.

If authentication fails, the function should throw a Response object, which will be sent to the client.

const server = new FastMCP({
  name: "My Server",
  version: "1.0.0",
  authenticate: (request) => {
    const apiKey = request.headers["x-api-key"];

    if (apiKey !== "123") {
      throw new Response(null, {
        status: 401,
        statusText: "Unauthorized",
      });
    }

    // Whatever you return here will be accessible in the `context.session` object.
    return {
      id: 1,
    };
  },
});

Now you can access the authenticated session data in your tools:

server.addTool({
  name: "sayHello",
  execute: async (args, { session }) => {
    return `Hello, ${session.id}!`;
  },
});

Tool Authorization

You can control which tools are available to authenticated users by adding an optional canAccess function to a tool's definition. This function receives the authentication context and should return true if the user is allowed to access the tool.

If canAccess is not provided, the tool is accessible to all authenticated users by default. If no authentication is configured on the server, all tools are available to all clients.

Example:

const server = new FastMCP<{ role: "admin" | "user" }>({
  authenticate: async (request) => {
    const role = request.headers["x-role"] as string;
    return { role: role === "admin" ? "admin" : "user" };
  },
  name: "My Server",
  version: "1.0.0",
});

server.addTool({
  name: "admin-dashboard",
  description: "An admin-only tool",
  // Only users with the 'admin' role can see and execute this tool
  canAccess: (auth) => auth?.role === "admin",
  execute: async () => {
    return "Welcome to the admin dashboard!";
  },
});

server.addTool({
  name: "public-info",
  description: "A tool available to everyone",
  execute: async () => {
    return "This is public information.";
  },
});

In this example, only clients authenticating with the admin role will be able to list or call the admin-dashboard tool. The public-info tool will be available to all authenticated users.

OAuth Proxy

FastMCP includes a built-in OAuth Proxy that acts as a secure intermediary between MCP clients and upstream OAuth providers. The proxy handles the complete OAuth 2.1 authorization flow, including Dynamic Client Registration (DCR), PKCE, consent management, and token management with encryption and token swap patterns enabled by default.

Key Features:

🔐 Secure by Default: Automatic encryption (AES-256-GCM) and token swap pattern
🚀 Zero Configuration: Auto-generates keys and handles OAuth flows automatically
🔌 Pre-configured Providers: Built-in support for Google, GitHub, and Azure
🎯 RFC Compliant: Implements DCR (RFC 7591), PKCE, and OAuth 2.1
🔑 Optional JWKS: Support for RS256/ES256 token verification (via optional jose dependency)

Quick Start:

import { FastMCP } from "fastmcp";
import { GoogleProvider } from "fastmcp/auth";

const authProxy = new GoogleProvider({
  clientId: process.env.GOOGLE_CLIENT_ID,
  clientSecret: process.env.GOOGLE_CLIENT_SECRET,
  baseUrl: "https://your-server.com",
  scopes: ["openid", "profile", "email"],
});

const server = new FastMCP({
  name: "My Server",
  oauth: {
    enabled: true,
    authorizationServer: authProxy.getAuthorizationServerMetadata(),
    proxy: authProxy, // Routes automatically registered!
  },
});

Documentation:

OAuth Proxy Features - Complete feature list and capabilities
OAuth Proxy Implementation Guide - Setup and configuration
Python vs TypeScript Comparison - Feature comparison

OAuth Discovery Endpoints

FastMCP also supports OAuth discovery endpoints for direct integration with OAuth providers, supporting both MCP Specification 2025-03-26 and MCP Specification 2025-06-18. This provides standard discovery endpoints that comply with RFC 8414 (OAuth 2.0 Authorization Server Metadata) and RFC 9470 (OAuth 2.0 Protected Resource Metadata):

import { FastMCP, DiscoveryDocumentCache } from "fastmcp";
import { buildGetJwks } from "get-jwks";
import fastJwt from "fast-jwt";

// Create a cache for discovery documents (reuse across requests)
const discoveryCache = new DiscoveryDocumentCache({
  ttl: 3600000, // Cache for 1 hour (default)
});

const server = new FastMCP({
  name: "My Server",
  version: "1.0.0",
  oauth: {
    enabled: true,
    authorizationServer: {
      issuer: "https://auth.example.com",
      authorizationEndpoint: "https://auth.example.com/oauth/authorize",
      tokenEndpoint: "https://auth.example.com/oauth/token",
      jwksUri: "https://auth.example.com/.well-known/jwks.json",
      responseTypesSupported: ["code"],
    },
    protectedResource: {
      resource: "mcp://my-server",
      authorizationServers: ["https://auth.example.com"],
    },
  },
  authenticate: async (request) => {
    const authHeader = request.headers.authorization;

    if (!authHeader?.startsWith("Bearer ")) {
      throw new Response(null, {
        status: 401,
        statusText: "Missing or invalid authorization header",
      });
    }

    const token = authHeader.slice(7); // Remove 'Bearer ' prefix

    // Validate OAuth JWT access token using OpenID Connect discovery
    try {
      // Fetch and cache the discovery document
      const discoveryUrl =
        "https://auth.example.com/.well-known/openid-configuration";
      // Alternative: Use OAuth authorization server metadata endpoint
      // const discoveryUrl = 'https://auth.example.com/.well-known/oauth-authorization-server';

      const config = (await discoveryCache.get(discoveryUrl)) as {
        jwks_uri: string;
        issuer: string;
      };
      const jwksUri = config.jwks_uri;
      const issuer = config.issuer;

      // Create JWKS client for token verification using discovered endpoint
      const getJwks = buildGetJwks({
        jwksUrl: jwksUri,
        cache: true,
        rateLimit: true,
      });

      // Create JWT verifier with JWKS and discovered issuer
      const verify = fastJwt.createVerifier({
        key: async (token) => {
          const { header } = fastJwt.decode(token, { complete: true });
          const jwk = await getJwks.getJwk({
            kid: header.kid,
            alg: header.alg,
          });
          return jwk;
        },
        algorithms: ["RS256", "ES256"],
        issuer: issuer,
        audience: "mcp://my-server",
      });

      // Verify the JWT token
      const payload = await verify(token);

      return {
        userId: payload.sub,
        scope: payload.scope,
        email: payload.email,
        // Include other claims as needed
      };
    } catch (error) {
      throw new Response(null, {
        status: 401,
        statusText: "Invalid OAuth token",
      });
    }
  },
});

This configuration automatically exposes OAuth discovery endpoints:

/.well-known/oauth-authorization-server - Authorization server metadata (RFC 8414)
/.well-known/oauth-protected-resource - Protected resource metadata (RFC 9728)
/.well-known/oauth-protected-resource<endpoint> - Protected resource metadata at sub-path (MCP 2025-11-25)

Discovery Mechanism (MCP Specification 2025-11-25):

Clients discover protected resource metadata using the following search order:

WWW-Authenticate header - Primary method (handled automatically by mcp-proxy)
Sub-path well-known - /.well-known/oauth-protected-resource<endpoint> (e.g., /.well-known/oauth-protected-resource/mcp)
Root well-known - /.well-known/oauth-protected-resource (fallback)

Both the sub-path and root endpoints return identical metadata, ensuring compatibility with all MCP client implementations.

For JWT token validation, you can use libraries like get-jwks and @fastify/jwt for OAuth JWT tokens.

Passing Headers Through Context

If you are exposing your MCP server via HTTP, you may wish to allow clients to supply sensitive keys via headers, which can then be passed along to APIs that your tools interact with, allowing each client to supply their own API keys. This can be done by capturing the HTTP headers in the authenticate section and storing them in the session to be referenced by the tools later.

import { FastMCP } from "fastmcp";
import { IncomingHttpHeaders } from "http";

// Define the session data type
interface SessionData {
  headers: IncomingHttpHeaders;
  [key: string]: unknown; // Add index signature to satisfy Record<string, unknown>
}

// Create a server instance
const server = new FastMCP({
  name: "My Server",
  version: "1.0.0",
  authenticate: async (request: any): Promise<SessionData> => {
    // Authentication logic
    return {
      headers: request.headers,
    };
  },
});

// Tool to display HTTP headers
server.addTool({
  name: "headerTool",
  description: "Reads HTTP headers from the request",
  execute: async (args: any, context: any) => {
    const session = context.session as SessionData;
    const headers = session?.headers ?? {};

    const getHeaderString = (header: string | string[] | undefined) =>
      Array.isArray(header) ? header.join(", ") : (header ?? "N/A");

    const userAgent = getHeaderString(headers["user-agent"]);
    const authorization = getHeaderString(headers["authorization"]);
    return `User-Agent: ${userAgent}\nAuthorization: ${authorization}\nAll Headers: ${JSON.stringify(headers, null, 2)}`;
  },
});

// Start the server
server.start({
  transportType: "httpStream",
  httpStream: {
    port: 8080,
  },
});

A client that would connect to this may look something like this:

import { StreamableHTTPClientTransport } from "@modelcontextprotocol/sdk/client/streamableHttp.js";
import { Client } from "@modelcontextprotocol/sdk/client/index.js";

const transport = new StreamableHTTPClientTransport(
  new URL(`http://localhost:8080/mcp`),
  {
    requestInit: {
      headers: {
        Authorization: "Test 123",
      },
    },
  },
);

const client = new Client({
  name: "example-client",
  version: "1.0.0",
});

(async () => {
  await client.connect(transport);

  // Call a tool
  const result = await client.callTool({
    name: "headerTool",
    arguments: {
      arg1: "value",
    },
  });

  console.log("Tool result:", result);
})().catch(console.error);

What would show up in the console after the client runs is something like this:

Tool result: {
  content: [
    {
      type: 'text',
      text: 'User-Agent: node\n' +
        'Authorization: Test 123\n' +
        'All Headers: {\n' +
        '  "host": "localhost:8080",\n' +
        '  "connection": "keep-alive",\n' +
        '  "authorization": "Test 123",\n' +
        '  "content-type": "application/json",\n' +
        '  "accept": "application/json, text/event-stream",\n' +
        '  "accept-language": "*",\n' +
        '  "sec-fetch-mode": "cors",\n' +
        '  "user-agent": "node",\n' +
        '  "accept-encoding": "gzip, deflate",\n' +
        '  "content-length": "163"\n' +
        '}'
    }
  ]
}

Session ID and Request ID Tracking

FastMCP automatically exposes session and request IDs to tool handlers through the context parameter. This enables per-session state management and request tracking.

Session ID (context.sessionId):

Available only for HTTP-based transports (HTTP Stream, SSE)
Extracted from the Mcp-Session-Id header
Remains constant across multiple requests from the same client
Useful for maintaining per-session state, counters, or user-specific data

Request ID (context.requestId):

Available for all transports when provided by the client
Unique for each individual request
Useful for request tracing and debugging

import { FastMCP } from "fastmcp";
import { z } from "zod";

const server = new FastMCP({
  name: "Session Counter Server",
  version: "1.0.0",
});

// Per-session counter storage
const sessionCounters = new Map<string, number>();

server.addTool({
  name: "increment_counter",
  description: "Increment a per-session counter",
  parameters: z.object({}),
  execute: async (args, context) => {
    if (!context.sessionId) {
      return "Session ID not available (requires HTTP transport)";
    }

    const counter = sessionCounters.get(context.sessionId) || 0;
    const newCounter = counter + 1;
    sessionCounters.set(context.sessionId, newCounter);

    return `Counter for session ${context.sessionId}: ${newCounter}`;
  },
});

server.addTool({
  name: "show_ids",
  description: "Display session and request IDs",
  parameters: z.object({}),
  execute: async (args, context) => {
    return `Session ID: ${context.sessionId || "N/A"}
Request ID: ${context.requestId || "N/A"}`;
  },
});

server.start({
  transportType: "httpStream",
  httpStream: {
    port: 8080,
  },
});

Use Cases:

Per-session state management: Maintain counters, caches, or temporary data unique to each client session
User authentication and authorization: Track authenticated users across requests
Session-specific resource management: Allocate and manage resources per session
Multi-tenant implementations: Isolate data and operations by session
Request tracing: Track individual requests for debugging and monitoring

Example:

See src/examples/session-id-counter.ts for a complete example demonstrating session-based counter management.

Notes:

Session IDs are automatically generated by the MCP transport layer
In stateless mode, session IDs are not persisted across requests
For stdio transport, sessionId will be undefined as there's no HTTP session concept

Providing Instructions

You can provide instructions to the server using the instructions option:

const server = new FastMCP({
  name: "My Server",
  version: "1.0.0",
  instructions:
    'Instructions describing how to use the server and its features.\n\nThis can be used by clients to improve the LLM\'s understanding of available tools, resources, etc. It can be thought of like a "hint" to the model. For example, this information MAY be added to the system prompt.',
});

Sessions

The session object is an instance of FastMCPSession and it describes active client sessions.

server.sessions;

We allocate a new server instance for each client connection to enable 1:1 communication between a client and the server.

Typed server events

You can listen to events emitted by the server using the on method:

server.on("connect", (event) => {
  console.log("Client connected:", event.session);
});

server.on("disconnect", (event) => {
  console.log("Client disconnected:", event.session);
});

`FastMCPSession`

FastMCPSession represents a client session and provides methods to interact with the client.

Refer to Sessions for examples of how to obtain a FastMCPSession instance.

`requestSampling`

requestSampling creates a sampling request and returns the response.

await session.requestSampling({
  messages: [
    {
      role: "user",
      content: {
        type: "text",
        text: "What files are in the current directory?",
      },
    },
  ],
  systemPrompt: "You are a helpful file system assistant.",
  includeContext: "thisServer",
  maxTokens: 100,
});

Options

requestSampling accepts an optional second parameter for request options:

await session.requestSampling(
  {
    messages: [
      {
        role: "user",
        content: {
          type: "text",
          text: "What files are in the current directory?",
        },
      },
    ],
    systemPrompt: "You are a helpful file system assistant.",
    includeContext: "thisServer",
    maxTokens: 100,
  },
  {
    // Progress callback - called when progress notifications are received
    onprogress: (progress) => {
      console.log(`Progress: ${progress.progress}/${progress.total}`);
    },

    // Abort signal for cancelling the request
    signal: abortController.signal,

    // Request timeout in milliseconds (default: DEFAULT_REQUEST_TIMEOUT_MSEC)
    timeout: 30000,

    // Whether progress notifications reset the timeout (default: false)
    resetTimeoutOnProgress: true,

    // Maximum total timeout regardless of progress (no default)
    maxTotalTimeout: 60000,
  },
);

Options:

onprogress?: (progress: Progress) => void - Callback for progress notifications from the remote end
signal?: AbortSignal - Abort signal to cancel the request
timeout?: number - Request timeout in milliseconds
resetTimeoutOnProgress?: boolean - Whether progress notifications reset the timeout
maxTotalTimeout?: number - Maximum total timeout regardless of progress notifications

`clientCapabilities`

The clientCapabilities property contains the client capabilities.

session.clientCapabilities;

`loggingLevel`

The loggingLevel property describes the logging level as set by the client.

session.loggingLevel;

`roots`

The roots property contains the roots as set by the client.

session.roots;

`server`

The server property contains an instance of MCP server that is associated with the session.

session.server;

Typed session events

You can listen to events emitted by the session using the on method:

session.on("rootsChanged", (event) => {
  console.log("Roots changed:", event.roots);
});

session.on("error", (event) => {
  console.error("Error:", event.error);
});

Running Your Server

Test with `mcp-cli`

The fastest way to test and debug your server is with fastmcp dev:

npx fastmcp dev server.js
npx fastmcp dev server.ts

This will run your server with mcp-cli for testing and debugging your MCP server in the terminal.

Inspect with `MCP Inspector`

Another way is to use the official MCP Inspector to inspect your server with a Web UI:

npx fastmcp inspect server.ts

FAQ

How to use with Claude Desktop?

Follow the guide https://modelcontextprotocol.io/quickstart/user and add the following configuration:

{
  "mcpServers": {
    "my-mcp-server": {
      "command": "npx",
      "args": ["tsx", "/PATH/TO/YOUR_PROJECT/src/index.ts"],
      "env": {
        "YOUR_ENV_VAR": "value"
      }
    }
  }
}

How to run FastMCP behind a proxy?

Refer to this issue for an example of using FastMCP with express and http-proxy-middleware.

Showcase

Note

If you've developed a server using FastMCP, please submit a PR to showcase it here!

Note

If you are looking for a boilerplate repository to build your own MCP server, check out fastmcp-boilerplate.

apinetwork/piapi-mcp-server - generate media using Midjourney/Flux/Kling/LumaLabs/Udio/Chrip/Trellis
domdomegg/computer-use-mcp - controls your computer
LiterallyBlah/Dradis-MCP – manages projects and vulnerabilities in Dradis
Meeting-Baas/meeting-mcp - create meeting bots, search transcripts, and manage recording data
drumnation/unsplash-smart-mcp-server – enables AI agents to seamlessly search, recommend, and deliver professional stock photos from Unsplash
ssmanji89/halopsa-workflows-mcp - HaloPSA Workflows integration with AI assistants
aiamblichus/mcp-chat-adapter – provides a clean interface for LLMs to use chat completion
eyaltoledano/claude-task-master – advanced AI project/task manager powered by FastMCP
cswkim/discogs-mcp-server - connects to the Discogs API for interacting with your music collection
Panzer-Jack/feuse-mcp - Frontend Useful MCP Tools - Essential utilities for web developers to automate API integration and code generation
sunra-ai/sunra-clients - Sunra.ai is a generative media platform built for developers, providing high-performance AI model inference capabilities.
foxtrottwist/shortcuts-mcp - connects Claude to macOS Shortcuts for system automation, app integration, and interactive workflows

Acknowledgements

FastMCP is inspired by the Python implementation by Jonathan Lowin.
Parts of codebase were adopted from LiteMCP.
Parts of codebase were adopted from Model Context protocolでSSEをやってみる.

Features

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