Show HN: Polymcp – Turn Any Python Function into an MCP Tool for AI Agents

Summary

I built Polymcp, a framework that allows you to transform any Python function into an MCP (Model Context Protocol) tool ready to be used by AI agents. No rewriting, no complex integrations.ExamplesSimple function:from polymcp.polymcp_toolkit import expose_tools_httpdef add(a: int, b: int) -> int: """Add two numbers""" return a + bapp = expose_tools_http([add], title="Math Tools")Run with:uvicorn server_mcp:app --reloadNow add is exposed via MCP and can be called directly by AI agents.API function:import requests from polymcp.polymcp_toolkit import expose_tools_httpdef 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_httpdef 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.Repo: https://github.com/poly-mcp/Polymcp