Show HN: Polymcp – Turn Any Python Function into an MCP Tool for AI Agents
Examples
Simple function:
from polymcp.polymcp_toolkit import expose_tools_http
def add(a: int, b: int) -> int: """Add two numbers""" return a + b
app = expose_tools_http([add], title="Math Tools")
Run with:
uvicorn server_mcp:app --reload
Now add is exposed via MCP and can be called directly by AI agents.
API function:
import requests from polymcp.polymcp_toolkit import expose_tools_http
def get_weather(city: str): """Return current weather data for a city""" response = requests.get(f"https://api.weatherapi.com/v1/current.json?q={city}") return response.json()
app = expose_tools_http([get_weather], title="Weather Tools")
AI agents can call get_weather("London") to get real-time weather data instantly.
Business workflow function:
import pandas as pd from polymcp.polymcp_toolkit import expose_tools_http
def calculate_commissions(sales_data: list[dict]): """Calculate sales commissions from sales data""" df = pd.DataFrame(sales_data) df["commission"] = df["sales_amount"] * 0.05 return df.to_dict(orient="records")
app = expose_tools_http([calculate_commissions], title="Business Tools")
AI agents can now generate commission reports automatically.
Why it matters for companies • Reuse existing code immediately: legacy scripts, internal libraries, APIs. • Automate complex workflows: AI can orchestrate multiple tools reliably. • Plug-and-play: multiple Python functions exposed on the same MCP server. • Reduce development time: no custom wrappers or middleware needed. • Built-in reliability: input/output validation and error handling included.
Polymcp makes Python functions immediately usable by AI agents, standardizing integration across enterprise software.