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# FastMCP
<!-- omit in toc -->
# FastMCP
> **Note**: This is experimental software. The Model Context Protocol itself is only a few days old and the specification is still evolving.
<div align="center">
A fast, pythonic way to build Model Context Protocol (MCP) servers.
[![PyPI - Version](https://img.shields.io/pypi/v/fastmcp.svg)](https://pypi.org/project/fastmcp)
[![Tests](https://github.com/jlowin/fastmcp/actions/workflows/run-tests.yml/badge.svg)](https://github.com/jlowin/fastmcp/actions/workflows/run-tests.yml)
[![License](https://img.shields.io/github/license/jlowin/fastmcp.svg)](https://github.com/jlowin/fastmcp/blob/main/LICENSE)
Anthropic's new [Model Context Protocol](https://modelcontextprotocol.io) is a powerful way to give broadcast new functionality and context to LLMs. However, developing MCP servers can be cumbersome. FastMCP provides a simple, intuitive interface for creating MCP servers in Python.
</div>
FastMCP is a high-level, intuitive framework for building [Model Context Protocol (MCP)](https://modelcontextprotocol.io) servers with Python. While MCP is a powerful protocol that enables LLMs to interact with local data and tools in a secure, standardized way, the specification can be cumbersome to implement directly. FastMCP lets you build fully compliant MCP servers in the most Pythonic way possible - in many cases, simply decorating a function is all that's required.
🚧 *Note: FastMCP is under active development, as is the low-level MCP Python SDK* 🏗️
Key features:
* **Intuitive**: Designed to feel familiar to Python developers, with powerful type hints and editor support
* **Simple**: Build compliant MCP servers with minimal boilerplate
* **Fast**: High-performance async implementation
* **Full-featured**: Complete implementation of the MCP specification
<!-- omit in toc -->
## Table of Contents
- [FastMCP](#fastmcp)
- [Table of Contents](#table-of-contents)
- [Installation](#installation)
- [Quick Start](#quick-start)
- [Core Concepts](#core-concepts)
- [Resources](#resources)
- [Tools](#tools)
- [Installation](#installation)
- [Quickstart](#quickstart)
- [What is MCP?](#what-is-mcp)
- [Core Concepts](#core-concepts)
- [Server](#server)
- [Resources](#resources)
- [Tools](#tools)
- [Prompts](#prompts)
- [Images](#images)
- [Context](#context)
- [Deployment](#deployment)
- [Development](#development)
- [Running the Dev Inspector](#running-the-dev-inspector)
- [Installing in Claude](#installing-in-claude)
- [License](#license)
- [Claude Desktop](#claude-desktop)
- [Examples](#examples)
- [Echo Server](#echo-server)
- [SQLite Explorer](#sqlite-explorer)
## Installation
MCP servers require you to use [uv](https://github.com/astral-sh/uv) as your dependency manager.
Install uv with brew:
```bash
brew install uv
```
*(Editor's note: I was unable to get MCP servers working unless uv was installed with brew.)*
Install FastMCP:
```bash
# We strongly recommend installing with uv
brew install uv # on macOS
uv pip install fastmcp
```
## Quick Start
Or with pip:
```bash
pip install fastmcp
```
Here's a simple example that exposes your desktop directory as a resource and provides a basic addition tool:
## Quickstart
Let's create a simple MCP server that exposes a calculator tool and some data:
```python
from pathlib import Path
from fastmcp import FastMCP
# Create server
# Create an MCP server
mcp = FastMCP("Demo")
@mcp.resource("dir://desktop")
def desktop() -> list[str]:
"""List the files in the user's desktop"""
desktop = Path.home() / "Desktop"
return [str(f) for f in desktop.iterdir()]
# Add an addition tool
@mcp.tool()
def add(a: int, b: int) -> int:
"""Add two numbers"""
return a + b
if __name__ == "__main__":
mcp.run()
# Add a dynamic greeting resource
@mcp.resource("greeting://{name}")
def get_greeting(name: str) -> str:
"""Get a personalized greeting"""
return f"Hello, {name}!"
```
To use this server, you have two options:
1. Install it in Claude Desktop:
```bash
fastmcp install server.py
```
2. Test it with the MCP Inspector:
```bash
fastmcp dev server.py
```
![MCP Inspector](docs/images/mcp-inspector.png)
## What is MCP?
The [Model Context Protocol (MCP)](https://modelcontextprotocol.io) lets you build servers that expose data and functionality to LLM applications in a secure, standardized way. Think of it like a web API, but specifically designed for LLM interactions. MCP servers can:
- Expose data through **Resources** (like GET endpoints)
- Provide functionality through **Tools** (like POST endpoints)
- Define interaction patterns through **Prompts** (reusable templates for LLM interactions)
## Core Concepts
FastMCP makes it easy to expose two types of functionality to LLMs: Resources and Tools.
*Note: All code examples below assume you've created a FastMCP server instance called `mcp`.*
### Server
The FastMCP server is your core interface to the MCP protocol. It handles connection management, protocol compliance, and message routing:
```python
from fastmcp import FastMCP
# Create a named server
mcp = FastMCP("My App")
# Configure host/port for HTTP transport (optional)
mcp = FastMCP("My App", host="localhost", port=8000)
```
### Resources
Resources are data sources that can be accessed by the LLM. They're perfect for providing context like files, API responses, or database queries.
Resources are how you expose data to LLMs. They're similar to GET endpoints in a REST API - they provide data but shouldn't perform significant computation or have side effects. Some examples:
FastMCP provides a simple `@resource` decorator that handles both static and dynamic resources. While the MCP spec distinguishes between resources and templates, FastMCP automatically handles this distinction based on your function signature:
- File contents
- Database schemas
- API responses
- System information
Resources can be static:
```python
# Static resource
@mcp.resource("resource://static")
def get_static() -> str:
"""Return static content"""
return "Static content"
# Dynamic resource
@mcp.resource("resource://{city}/weather")
def get_weather(city: str) -> str:
"""Get weather for a city"""
return f"Weather for {city}"
# Multiple parameters are supported
@mcp.resource("db://users/{user_id}/posts/{post_id}")
def get_user_post(user_id: int, post_id: int) -> dict:
"""Get a specific post by a user"""
return {
"user_id": user_id,
"post_id": post_id,
"content": "Post content..."
}
# File resources
@mcp.resource("file://config.json")
@mcp.resource("config://app")
def get_config() -> str:
"""Read the config file"""
return Path("config.json").read_text()
"""Static configuration data"""
return "App configuration here"
```
Resources can return:
- Strings for text content
- Bytes for binary content
- Other types will be converted to JSON
When your resource URI includes parameters in curly braces (like `{city}`) and your function accepts matching arguments, FastMCP automatically sets up a template resource behind the scenes. This means you don't need to worry about the distinction between resources and templates in the MCP spec - just write your function, and FastMCP handles the rest.
> **Note**: If you're familiar with the MCP spec, you might notice that dynamic resources are implemented as templates under the hood. FastMCP simplifies this by providing a unified interface through the `@resource` decorator. This is similar to how web frameworks often unify GET and POST handlers under a single route decorator.
Or dynamic with parameters (FastMCP automatically handles these as MCP templates):
```python
@mcp.resource("users://{user_id}/profile")
def get_user_profile(user_id: str) -> str:
"""Dynamic user data"""
return f"Profile data for user {user_id}"
```
### Tools
Tools are functions that can be called by the LLM to perform actions. They're great for calculations, API calls, or any interactive functionality. Tools are defined using the `@tool` decorator:
Tools let LLMs take actions through your server. Unlike resources, tools are expected to perform computation and have side effects. They're similar to POST endpoints in a REST API.
Simple calculation example:
```python
@mcp.tool()
def search_docs(query: str, max_results: int = 5) -> list[dict]:
"""Search documentation for relevant entries"""
results = perform_search(query, limit=max_results)
return [{"title": r.title, "excerpt": r.excerpt} for r in results]
def calculate_bmi(weight_kg: float, height_m: float) -> float:
"""Calculate BMI given weight in kg and height in meters"""
return weight_kg / (height_m ** 2)
```
HTTP request example:
```python
import httpx
@mcp.tool()
def analyze_image(image_path: str) -> dict:
"""Analyze an image and return metadata"""
from PIL import Image
img = Image.open(image_path)
return {
"size": img.size,
"mode": img.mode,
"format": img.format
}
async def fetch_weather(city: str) -> str:
"""Fetch current weather for a city"""
async with httpx.AsyncClient() as client:
response = await client.get(
f"https://api.weather.com/{city}"
)
return response.text
```
Tools support:
- Type hints for parameters
- Default values
- Async functions
- Return value conversion to JSON
### Prompts
## Development
Prompts are reusable templates that help LLMs interact with your server effectively. They're like "best practices" encoded into your server. A prompt can be as simple as a string:
FastMCP includes developer tools to make testing and debugging easier.
```python
@mcp.prompt()
def review_code(code: str) -> str:
return f"Please review this code:\n\n{code}"
```
### Running the Dev Inspector
Or a more structured sequence of messages:
```python
from fastmcp.prompts.base import UserMessage, AssistantMessage
The MCP Inspector helps you test your server during development:
@mcp.prompt()
def debug_error(error: str) -> list[Message]:
return [
UserMessage("I'm seeing this error:"),
UserMessage(error),
AssistantMessage("I'll help debug that. What have you tried so far?")
]
```
### Images
FastMCP provides an `Image` class that automatically handles image data in your server:
```python
from fastmcp import FastMCP, Image
from PIL import Image as PILImage
@mcp.tool()
def create_thumbnail(image_path: str) -> Image:
"""Create a thumbnail from an image"""
img = PILImage.open(image_path)
img.thumbnail((100, 100))
# FastMCP automatically handles conversion and MIME types
return Image(data=img.tobytes(), format="png")
@mcp.tool()
def load_image(path: str) -> Image:
"""Load an image from disk"""
# FastMCP handles reading and format detection
return Image(path=path)
```
Images can be used as the result of both tools and resources.
### Context
The Context object gives your tools and resources access to MCP capabilities. To use it, add a parameter annotated with `fastmcp.Context`:
```python
from fastmcp import FastMCP, Context
@mcp.tool()
async def long_task(files: list[str], ctx: Context) -> str:
"""Process multiple files with progress tracking"""
for i, file in enumerate(files):
ctx.info(f"Processing {file}")
await ctx.report_progress(i, len(files))
# Read another resource if needed
data = await ctx.read_resource(f"file://{file}")
return "Processing complete"
```
The Context object provides:
- Progress reporting through `report_progress()`
- Logging via `debug()`, `info()`, `warning()`, and `error()`
- Resource access through `read_resource()`
- Request metadata via `request_id` and `client_id`
## Deployment
The FastMCP CLI helps you develop and deploy MCP servers.
Note that for all deployment commands, you are expected to provide the fully qualified path to your server object. For example, if you have a file `server.py` that contains a FastMCP server named `my_server`, you would provide `path/to/server.py:my_server`.
If your server variable has one of the standard names (`mcp`, `server`, or `app`), you can omit the server name from the path and just provide the file: `path/to/server.py`.
### Development
Test and debug your server with the MCP Inspector:
```bash
# Provide the fully qualified path to your server
fastmcp dev server.py:my_mcp_server
# Or just the file if your server is named 'mcp', 'server', or 'app'
fastmcp dev server.py
```
Your server is run in an isolated environment, so you'll need to indicate any dependencies with the `--with` flag. FastMCP is automatically included. If you are working on a uv project, you can use the `--with-editable` flag to mount your current directory:
```bash
# Basic usage
fastmcp dev your_server.py
# With additional packages
fastmcp dev server.py --with pandas --with numpy
# Install package in editable mode from current directory
fastmcp dev your_server.py --with-editable .
# Install additional packages
fastmcp dev your_server.py --with pandas --with numpy
# Combine both
fastmcp dev your_server.py --with-editable . --with pandas --with numpy
# Using your project's dependencies and up-to-date code
fastmcp dev server.py --with-editable .
```
The `--with` flag automatically includes `fastmcp` and any additional packages you specify. The `--with-editable` flag installs the package from the specified directory in editable mode, which is useful during development.
### Installing in Claude
To use your server with Claude Desktop:
### Claude Desktop
Install your server in Claude Desktop:
```bash
# Basic usage
fastmcp install your_server.py --name "My Server"
# Basic usage (name is taken from your FastMCP instance)
fastmcp install server.py
# Install package in editable mode
fastmcp install your_server.py --with-editable .
# With a custom name
fastmcp install server.py --name "My Server"
# Install additional packages
fastmcp install your_server.py --with pandas --with numpy
# With dependencies
fastmcp install server.py --with pandas --with numpy
# Combine options
fastmcp install your_server.py --with-editable . --with pandas --with numpy
# Replace an existing server
fastmcp install server.py --force
```
## License
The server name in Claude will be:
1. The `--name` parameter if provided
2. The `name` from your FastMCP instance
3. The filename if the server can't be imported
Apache 2.0
## Examples
### Echo Server
A simple server demonstrating resources, tools, and prompts:
```python
from fastmcp import FastMCP
mcp = FastMCP("Echo")
@mcp.resource("echo://{message}")
def echo_resource(message: str) -> str:
"""Echo a message as a resource"""
return f"Resource echo: {message}"
@mcp.tool()
def echo_tool(message: str) -> str:
"""Echo a message as a tool"""
return f"Tool echo: {message}"
@mcp.prompt()
def echo_prompt(message: str) -> str:
"""Create an echo prompt"""
return f"Please process this message: {message}"
```
### SQLite Explorer
A more complex example showing database integration:
```python
from fastmcp import FastMCP
import sqlite3
mcp = FastMCP("SQLite Explorer")
@mcp.resource("schema://main")
def get_schema() -> str:
"""Provide the database schema as a resource"""
conn = sqlite3.connect("database.db")
schema = conn.execute(
"SELECT sql FROM sqlite_master WHERE type='table'"
).fetchall()
return "\n".join(sql[0] for sql in schema if sql[0])
@mcp.tool()
def query_data(sql: str) -> str:
"""Execute SQL queries safely"""
conn = sqlite3.connect("database.db")
try:
result = conn.execute(sql).fetchall()
return "\n".join(str(row) for row in result)
except Exception as e:
return f"Error: {str(e)}"
@mcp.prompt()
def analyze_table(table: str) -> str:
"""Create a prompt template for analyzing tables"""
return f"""Please analyze this database table:
Table: {table}
Schema:
{get_schema()}
What insights can you provide about the structure and relationships?"""
```

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from fastmcp import FastMCP
# Create an MCP server
mcp = FastMCP("Demo")
# Add an addition tool
@mcp.tool()
def add(a: int, b: int) -> int:
"""Add two numbers"""
return a + b
# Add a dynamic greeting resource
@mcp.resource("greeting://{name}")
def get_greeting(name: str) -> str:
"""Get a personalized greeting"""
return f"Hello, {name}!"

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src/fastmcp/resources/base.py
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@ -27,14 +27,8 @@ class Resource(BaseModel, abc.ABC):
"""Set default name from URI if not provided."""
if name:
return name
# Extract everything after the protocol (e.g., "desktop" from "resource://desktop")
uri = info.data.get("uri")
if uri:
uri_str = str(uri)
if "://" in uri_str:
name = uri_str.split("://", 1)[1]
if name:
return name
if uri := info.data.get("uri"):
return str(uri)
raise ValueError("Either name or uri must be provided")
@abc.abstractmethod

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tests/resources/test_resources.py
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@ -45,7 +45,7 @@ class TestResourceValidation:
uri="resource://my-resource",
fn=dummy_func,
)
assert resource.name == "my-resource"
assert resource.name == "resource://my-resource"
def test_resource_name_validation(self):
"""Test name validation."""