MCP vs OpenAI Function Calling

weather_openai.py

import openai
import json
import requests

# Define function schema
tools = [
    {
        "type": "function",
        "function": {
            "name": "get_weather",
            "description": "Get current weather for a location",
            "parameters": {
                "type": "object",
                "properties": {
                    "location": {
                        "type": "string",
                        "description": "City name, e.g. San Francisco"
                    },
                    "unit": {
                        "type": "string",
                        "enum": ["celsius", "fahrenheit"],
                        "description": "Temperature unit"
                    }
                },
                "required": ["location"]
            }
        }
    }
]

# Function implementation
def get_weather(location, unit="celsius"):
    # Call weather API
    response = requests.get(
        f"https://api.weather.com/v1/current",
        params={"location": location, "unit": unit}
    )
    return response.json()

# Chat completion with function calling
response = openai.chat.completions.create(
    model="gpt-4",
    messages=[
        {"role": "user", "content": "What's the weather in Tokyo?"}
    ],
    tools=tools,
    tool_choice="auto"
)

# Handle function call
if response.choices[0].message.tool_calls:
    tool_call = response.choices[0].message.tool_calls[0]
    function_name = tool_call.function.name
    function_args = json.loads(tool_call.function.arguments)

    # Execute function
    if function_name == "get_weather":
        result = get_weather(**function_args)

        # Send result back to model
        second_response = openai.chat.completions.create(
            model="gpt-4",
            messages=[
                {"role": "user", "content": "What's the weather in Tokyo?"},
                response.choices[0].message,
                {
                    "role": "tool",
                    "tool_call_id": tool_call.id,
                    "content": json.dumps(result)
                }
            ]
        )
        print(second_response.choices[0].message.content)

weather_mcp.py

from mcp.server import Server
from mcp.types import Tool, TextContent
import requests

server = Server("weather-server")

@server.tool()
async def get_weather(location: str, unit: str = "celsius") -> str:
    """Get current weather for a location

    Args:
        location: City name, e.g. San Francisco
        unit: Temperature unit (celsius or fahrenheit)
    """
    response = requests.get(
        f"https://api.weather.com/v1/current",
        params={"location": location, "unit": unit}
    )

    data = response.json()
    return f"Temperature in {location}: {data['temp']}°{unit[0].upper()}"

if __name__ == "__main__":
    server.run()

Configure in Claude Desktop

{
  "mcpServers": {
    "weather": {
      "command": "python",
      "args": ["weather_mcp.py"]
    }
  }
}

Before (OpenAI)

def send_email(to, subject, body):
    # Your email logic
    return {"status": "sent"}

# In your API route
if function_name == "send_email":
    result = send_email(**args)

After (MCP Server)

from mcp.server import Server

server = Server("email-server")

@server.tool()
async def send_email(to: str, subject: str, body: str) -> str:
    """Send an email

    Args:
        to: Recipient email address
        subject: Email subject line
        body: Email content
    """
    # Your email logic (same as before)
    return "Email sent successfully"