prefecthq--fastmcp/docs/v2/getting-started/welcome.mdx

---
title: "Welcome to FastMCP 2.0!"
sidebarTitle: "Welcome!"
description: The fast, Pythonic way to build MCP servers and clients.
icon: hand-wave
---

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**FastMCP is the standard framework for building MCP applications.** The [Model Context Protocol](https://modelcontextprotocol.io/) (MCP) provides a standardized way to connect LLMs to tools and data, and FastMCP makes it production-ready with clean, Pythonic code:

```python {1}
from fastmcp import FastMCP

mcp = FastMCP("Demo 🚀")

@mcp.tool
def add(a: int, b: int) -> int:
    """Add two numbers"""
    return a + b

if __name__ == "__main__":
    mcp.run()
```

## Beyond Basic MCP

FastMCP pioneered Python MCP development, and FastMCP 1.0 was incorporated into the [official MCP SDK](https://github.com/modelcontextprotocol/python-sdk) in 2024.

**This is FastMCP 2.0,** the actively maintained version that extends far beyond basic protocol implementation. While the SDK provides core functionality, FastMCP 2.0 delivers everything needed for production: advanced MCP patterns (server composition, proxying, OpenAPI/FastAPI generation, tool transformation), enterprise auth (Google, GitHub, Azure, Auth0, WorkOS, and more), deployment tools, testing frameworks, and comprehensive client libraries.

Ready to build? Start with our [installation guide](/v2/getting-started/installation) or jump straight to the [quickstart](/v2/getting-started/quickstart).

FastMCP is made with 💙 by [Prefect](https://www.prefect.io/).

<Warning>
**FastMCP 3.0** is in development and may include breaking changes. To avoid unexpected issues, pin your dependency to v2: `fastmcp<3`
</Warning>

## What is MCP?

The Model Context Protocol lets you build servers that expose data and functionality to LLM applications in a secure, standardized way. It is often described as "the USB-C port for AI", providing a uniform way to connect LLMs to resources they can use. It may be easier to think of it as an API, but specifically designed for LLM interactions. MCP servers can:

- Expose data through `Resources` (think of these sort of like GET endpoints; they are used to load information into the LLM's context)
- Provide functionality through `Tools` (sort of like POST endpoints; they are used to execute code or otherwise produce a side effect)
- Define interaction patterns through `Prompts` (reusable templates for LLM interactions)
- And more!

FastMCP provides a high-level, Pythonic interface for building, managing, and interacting with these servers.

## Why FastMCP?

FastMCP handles all the complex protocol details so you can focus on building. In most cases, decorating a Python function is all you need — FastMCP handles the rest.

🚀 **Fast**: High-level interface means less code and faster development

🍀 **Simple**: Build MCP servers with minimal boilerplate

🐍 **Pythonic**: Feels natural to Python developers

🔍 **Complete**: Everything for production — enterprise auth (Google, GitHub, Azure, Auth0, WorkOS), deployment tools, testing frameworks, client libraries, and more

FastMCP provides the shortest path from idea to production. Deploy locally, to the cloud with [Prefect Horizon](https://horizon.prefect.io?utm_source=gofastmcp&utm_medium=docs) (free for personal projects), or to your own infrastructure.

<Tip>
**This documentation reflects FastMCP's `main` branch**, meaning it always reflects the latest development version. Features are generally marked with version badges (e.g. `New in version: 2.13.1`) to indicate when they were introduced. Note that this may include features that are not yet released.
</Tip>

## LLM-Friendly Docs

The FastMCP documentation is available in multiple LLM-friendly formats:

### MCP Server

The FastMCP docs are accessible via MCP! The server URL is `https://gofastmcp.com/mcp`. 

In fact, you can use FastMCP to search the FastMCP docs:

```python
import asyncio
from fastmcp import Client

async def main():
    async with Client("https://gofastmcp.com/mcp") as client:
        result = await client.call_tool(
            name="search_fast_mcp",
            arguments={"query": "deploy a FastMCP server"}
        )
    print(result)

asyncio.run(main())
```

### Text Formats

The docs are also available in [llms.txt format](https://llmstxt.org/):
- [llms.txt](https://gofastmcp.com/llms.txt) - A sitemap listing all documentation pages
- [llms-full.txt](https://gofastmcp.com/llms-full.txt) - The entire documentation in one file (may exceed context windows)

Any page can be accessed as markdown by appending `.md` to the URL. For example, this page becomes `https://gofastmcp.com/getting-started/welcome.md`.

You can also copy any page as markdown by pressing "Cmd+C" (or "Ctrl+C" on Windows) on your keyboard.