Package Exports

fastmcp
fastmcp/dist/FastMCP.js

This package does not declare an exports field, so the exports above have been automatically detected and optimized by JSPM instead. If any package subpath is missing, it is recommended to post an issue to the original package (fastmcp) to support the "exports" field. If that is not possible, create a JSPM override to customize the exports field for this package.

Readme

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
Sessions
Image content
Audio content
Embedded
Logging
Error handling
HTTP Streaming (with SSE compatibility)
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

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/stream.

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/stream`),
);

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);

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.

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,
  //     ],
  //   };
  // },
});

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 }) => {
    reportProgress({
      progress: 0,
      total: 100,
    });

    // ...

    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 allows you to authenticate clients using a custom function:

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}!`;
  },
});

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,
});

`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"
      }
    }
  }
}

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

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.

fastmcp