Building a Custom MCP Server: A Python Calculator (Step-by-Step)

✅ Prerequisites

Before we begin, make sure you have:

• 🐍 Python 3.10+ installed
• 💻 A code editor (VS Code, etc.)
• 🖥️ Basic command line knowledge

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🛠️ Step 1: Environment Setup

First, let's create a directory for our project and set up a clean Python environment.

Open your terminal and run:

# 1. Create the project folder
mkdir mcp-unit-converter
cd mcp-unit-converter

# 2. Create a virtual environment
python -m venv venv

3. Activate the environment:

On Windows:

venv\Scripts\activate

On Mac/Linux:

source venv/bin/activate

4. Install the MCP SDK:

pip install mcp[cli]

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📝 Step 2: Writing the Server Code

We will use the FastMCP class to build our server quickly. Create a file named converter.py.

This code defines tools for converting:

• 🌡️ Temperature (Celsius/Fahrenheit)
• 📏 Length (Meters/Feet)
• ⚖️ Weight (Kg/Pounds)

from mcp.server.fastmcp import FastMCP

# Initialize the server
mcp = FastMCP("UnitConverter")

# --- Temperature Tools ---

@mcp.tool()
def celsius_to_fahrenheit(celsius: float) -> float:
    """Convert Celsius to Fahrenheit"""
    return (celsius * 9/5) + 32

@mcp.tool()
def fahrenheit_to_celsius(fahrenheit: float) -> float:
    """Convert Fahrenheit to Celsius"""
    return (fahrenheit - 32) * 5/9

# --- Length Tools ---

@mcp.tool()
def meters_to_feet(meters: float) -> float:
    """Convert Meters to Feet"""
    return meters * 3.28084

@mcp.tool()
def feet_to_meters(feet: float) -> float:
    """Convert Feet to Meters"""
    return feet / 3.28084

# --- Weight Tools ---

@mcp.tool()
def kg_to_pounds(kg: float) -> float:
    """Convert Kilograms to Pounds"""
    return kg * 2.20462

@mcp.tool()
def pounds_to_kg(pounds: float) -> float:
    """Convert Pounds to Kilograms"""
    return pounds / 2.20462

if __name__ == "__main__":
    mcp.run(transport="stdio")

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🧪 Step 3: Testing with MCP Inspector

Before connecting it to an AI, let's verify it works locally using the MCP Inspector.

Run this command in your terminal:

mcp dev converter.py

This will open a local web interface. You can:

1. Select the celsius_to_fahrenheit tool
2. Input 0
3. Check if it returns 32 ✅

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🔗 Step 4: Connecting to an AI Client

Now for the magic! ✨ We will connect our server to any MCP-compliant client.

Configuration Steps:

1. Locate your client's MCP configuration folder
2. Create or edit your mcp.json configuration file
3. Add the following configuration:

{
  "mcpServers": {
    "unit_converter": {
      "command": "/ABSOLUTE/PATH/TO/YOUR/venv/bin/python",
      "args": ["/ABSOLUTE/PATH/TO/YOUR/converter.py"]
    }
  }
}

⚠️ Important: You must use the absolute path to your python executable inside the venv folder and the absolute path to your converter.py file.

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🎬 Step 5: Seeing it in Action

Once connected, you can open your AI Chat and ask:

"I have a shipping crate that weighs 450 kg and is 12 meters long. Convert these to pounds and feet using my tools."

The AI will intelligently call kg_to_pounds and meters_to_feet and give you the exact result based on your code.

Example Output:

Input	Tool Used	Result
450 kg	kg_to_pounds	992.08 lbs
12 m	meters_to_feet	39.37 ft

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📦 Source Code

You can find the complete repository with the source code here:

🔗 GitHub: https://github.com/GregoBHM/mcp-unit-converter

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🎯 Conclusion

Building an MCP server is surprisingly simple. With just a few lines of Python, we extended the capabilities of our AI assistant, making it more reliable for specific tasks like unit conversion.

What We Learned:

• ✅ How to set up an MCP server with Python
• ✅ How to define custom tools using @mcp.tool() decorator
• ✅ How to test locally with MCP Inspector
• ✅ How to connect to an MCP-compliant AI client

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If you found this useful, check out the video demonstration below! 🎥

Happy coding! 🚀