prefecthq--fastmcp/docs/tutorials/create-mcp-server.mdx

---
title: "How to Create an MCP Server in Python"
sidebarTitle: "Creating an MCP Server"
description: "A step-by-step guide to building a Model Context Protocol (MCP) server using Python and FastMCP, from basic tools to dynamic resources."
icon: server
---

So you want to build a Model Context Protocol (MCP) server in Python. The goal is to create a service that can provide tools and data to AI models like Claude, Gemini, or others that support the protocol. While the [MCP specification](https://modelcontextprotocol.io/specification/) is powerful, implementing it from scratch involves a lot of boilerplate: handling JSON-RPC, managing session state, and correctly formatting requests and responses.

This is where **FastMCP** comes in. It's a high-level framework that handles all the protocol complexities for you, letting you focus on what matters: writing the Python functions that power your server.

This guide will walk you through creating a fully-featured MCP server from scratch using FastMCP.

<Tip>
Every code block in this tutorial is a complete, runnable example. You can copy and paste it into a file and run it, or paste it directly into a Python REPL like IPython to try it out.
</Tip>

### Prerequisites

Make sure you have FastMCP installed. If not, follow the [installation guide](/getting-started/installation).

```bash
pip install fastmcp
```


## Step 1: Create the Basic Server

Every FastMCP application starts with an instance of the `FastMCP` class. This object acts as the container for all your tools and resources.

Create a new file called `my_mcp_server.py`:

```python my_mcp_server.py
from fastmcp import FastMCP

# Create a server instance with a descriptive name
mcp = FastMCP(name="My First MCP Server")
```

That's it! You have a valid (though empty) MCP server. Now, let's add some functionality.

## Step 2: Add a Tool

Tools are functions that an LLM can execute. Let's create a simple tool that adds two numbers.

To do this, simply write a standard Python function and decorate it with `@mcp.tool`.

```python my_mcp_server.py {5-8}
from fastmcp import FastMCP

mcp = FastMCP(name="My First MCP Server")

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

FastMCP automatically handles the rest:
- **Tool Name:** It uses the function name (`add`) as the tool's name.
- **Description:** It uses the function's docstring as the tool's description for the LLM.
- **Schema:** It inspects the type hints (`a: int`, `b: int`) to generate a JSON schema for the inputs.

This is the core philosophy of FastMCP: **write Python, not protocol boilerplate.**

## Step 3: Expose Data with Resources

Resources provide read-only data to the LLM. You can define a resource by decorating a function with `@mcp.resource`, providing a unique URI.

Let's expose a simple configuration dictionary as a resource.

```python my_mcp_server.py {10-13}
from fastmcp import FastMCP

mcp = FastMCP(name="My First MCP Server")

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

@mcp.resource("resource://config")
def get_config() -> dict:
    """Provides the application's configuration."""
    return {"version": "1.0", "author": "MyTeam"}
```

When a client requests the URI `resource://config`, FastMCP will execute the `get_config` function and return its output (serialized as JSON) to the client. The function is only called when the resource is requested, enabling lazy-loading of data.

## Step 4: Generate Dynamic Content with Resource Templates

Sometimes, you need to generate resources based on parameters. This is what **Resource Templates** are for. You define them using the same `@mcp.resource` decorator but with placeholders in the URI.

Let's create a template that provides a personalized greeting.

```python my_mcp_server.py {15-17}
from fastmcp import FastMCP

mcp = FastMCP(name="My First MCP Server")

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

@mcp.resource("resource://config")
def get_config() -> dict:
    """Provides the application's configuration."""
    return {"version": "1.0", "author": "MyTeam"}

@mcp.resource("greetings://{name}")
def personalized_greeting(name: str) -> str:
    """Generates a personalized greeting for the given name."""
    return f"Hello, {name}! Welcome to the MCP server."
```

Now, clients can request dynamic URIs:
- `greetings://Ford` will call `personalized_greeting(name="Ford")`.
- `greetings://Marvin` will call `personalized_greeting(name="Marvin")`.

FastMCP automatically maps the `{name}` placeholder in the URI to the `name` parameter in your function.

## Step 5: Run the Server

To make your server executable, add a `__main__` block to your script that calls `mcp.run()`.

```python my_mcp_server.py {19-20}
from fastmcp import FastMCP

mcp = FastMCP(name="My First MCP Server")

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

@mcp.resource("resource://config")
def get_config() -> dict:
    """Provides the application's configuration."""
    return {"version": "1.0", "author": "MyTeam"}

@mcp.resource("greetings://{name}")
def personalized_greeting(name: str) -> str:
    """Generates a personalized greeting for the given name."""
    return f"Hello, {name}! Welcome to the MCP server."

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

Now you can run your server from the command line:
```bash
python my_mcp_server.py
```
This starts the server using the default **STDIO transport**, which is how clients like Claude Desktop communicate with local servers. To learn about other transports, like HTTP, see the [Running Your Server](/deployment/running-server) guide.

## The Complete Server

Here is the full code for `my_mcp_server.py` (click to expand):

```python my_mcp_server.py [expandable]
from fastmcp import FastMCP

# 1. Create the server
mcp = FastMCP(name="My First MCP Server")

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

# 3. Add a static resource
@mcp.resource("resource://config")
def get_config() -> dict:
    """Provides the application's configuration."""
    return {"version": "1.0", "author": "MyTeam"}

# 4. Add a resource template for dynamic content
@mcp.resource("greetings://{name}")
def personalized_greeting(name: str) -> str:
    """Generates a personalized greeting for the given name."""
    return f"Hello, {name}! Welcome to the MCP server."

# 5. Make the server runnable
if __name__ == "__main__":
    mcp.run()
```

## Next Steps

You've successfully built an MCP server! From here, you can explore more advanced topics:

-   [**Tools in Depth**](/servers/tools): Learn about asynchronous tools, error handling, and custom return types.
-   [**Resources & Templates**](/servers/resources): Discover different resource types, including files and HTTP endpoints.
-   [**Prompts**](/servers/prompts): Create reusable prompt templates for your LLM.
-   [**Running Your Server**](/deployment/running-server): Deploy your server with different transports like HTTP.