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poly-mcp
polymcp
HISTORICAL RECORD2025–2026
poly-mcp / polymcp · Not publicly available

polymcp

Discover this repository through its Hacker News conversations.

2Distinct people
26Mentions
0Explicit recommenders
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This week on Hacker News

Nov 8–Nov 15 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/15/2026, 8:27:21 AM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by week26 dated mentions

Observed mentions: 2025-11-29 15:28:11 UTC to 2026-02-19 22:07:49 UTC. Weeks start Monday, UTC.

02462025-11-24 00:00:00 UTC to 2025-12-01 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 commentsNov 242025-12-01 00:00:00 UTC to 2025-12-08 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-12-08 00:00:00 UTC to 2025-12-15 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-12-15 00:00:00 UTC to 2025-12-22 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-12-22 00:00:00 UTC to 2025-12-29 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-12-29 00:00:00 UTC to 2026-01-05 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2026-01-05 00:00:00 UTC to 2026-01-12 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 commentsJan 52026-01-12 00:00:00 UTC to 2026-01-19 00:00:00 UTC (exclusive): 4 mentions; 4 submissions, 0 comments2026-01-19 00:00:00 UTC to 2026-01-26 00:00:00 UTC (exclusive): 5 mentions; 5 submissions, 0 comments2026-01-26 00:00:00 UTC to 2026-02-02 00:00:00 UTC (exclusive): 4 mentions; 4 submissions, 0 comments2026-02-02 00:00:00 UTC to 2026-02-09 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 comments2026-02-09 00:00:00 UTC to 2026-02-16 00:00:00 UTC (exclusive): 7 mentions; 6 submissions, 1 comments2026-02-16 00:00:00 UTC to 2026-02-23 00:00:00 UTC (exclusive): 3 mentions; 3 submissions, 0 commentsFeb 16

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
Nov 242025-11-24 00:00:00 UTC2025-12-01 00:00:00 UTC110
Dec 12025-12-01 00:00:00 UTC2025-12-08 00:00:00 UTC000
Dec 82025-12-08 00:00:00 UTC2025-12-15 00:00:00 UTC000
Dec 152025-12-15 00:00:00 UTC2025-12-22 00:00:00 UTC000
Dec 222025-12-22 00:00:00 UTC2025-12-29 00:00:00 UTC000
Dec 292025-12-29 00:00:00 UTC2026-01-05 00:00:00 UTC101
Jan 52026-01-05 00:00:00 UTC2026-01-12 00:00:00 UTC000
Jan 122026-01-12 00:00:00 UTC2026-01-19 00:00:00 UTC440
Jan 192026-01-19 00:00:00 UTC2026-01-26 00:00:00 UTC550
Jan 262026-01-26 00:00:00 UTC2026-02-02 00:00:00 UTC440
Feb 22026-02-02 00:00:00 UTC2026-02-09 00:00:00 UTC110
Feb 92026-02-09 00:00:00 UTC2026-02-16 00:00:00 UTC761
Feb 162026-02-16 00:00:00 UTC2026-02-23 00:00:00 UTC330

What Hacker News says

4 sources
justvugg·Feb 1, 2026Submission

Show HN: PolyMCP – Expose Python/TS functions as MCP tools easily

I built PolyMCP to make it trivial to expose existing functions as MCP tools, without rewriting logic or adding much glue code. The goal: take “normal” Python or TypeScript functions and instantly make them usable by MCP clients (Claude Desktop, agents, Ollama, etc.). Python example from polymcp.polymcp_toolkit import expose_tools def greet(name: str) -> str: """Say hello.""" return f"Hello, {name}!" def add(a: int, b: int) -> int: """Add two numbers.""" return a + b app = expose_tools([greet, add], title="My MCP Tools") Run with: uvicorn server:app --reload MCP endpoints appear at: • /mcp/list_tools • /mcp/invoke TypeScript example import { z } from "zod"; import { tool, exposeTools } from "polymcp"; const uppercaseTool = tool({ name: "uppercase", description: "Convert text to uppercase", inputSchema: z.object({ t
Read the rest
ext: z.string() }), function: async ({ text }) => text.toUpperCase(), }); const app = exposeTools([uppercaseTool], { title: "Text Tools" }); app.listen(3000); More “real” example (Python) import pandas as pd from polymcp.polymcp_toolkit import expose_tools def calculate_commissions(sales_data: list[dict]): df = pd.DataFrame(sales_data) df["commission"] = df["sales_amount"] * 0.05 return df.to_dict(orient="records") app = expose_tools([calculate_commissions], title="Business Tools") What you get • Reuse existing code with minimal changes • MCP-compatible (Claude Desktop, agents, Ollama, etc.) • HTTP, stdio, and WASM support • Automatic input validation • Basic production features (budgets, retries, redaction, logs) • Built-in inspector for testing and monitoring Install • Python: pip install polymcp • TypeScript: clone repo → cd polymcp-ts → npm install → npm run build Repo: https://github.com/poly-mcp/Polymcp Curious what kind of function people would expose first if it was this easy. Feedback very welcome.
1 points · Open discussion
justvugg·Jan 28, 2026Submission

Show HN: PolyMCP – Expose Python/TS functions as MCP tools easily

I made PolyMCP so I could quickly turn normal functions (Python or TypeScript) into MCP tools without much extra work. Python example: from polymcp.polymcp_toolkit import expose_tools def greet(name: str) -> str: """Say hello.""" return f"Hello, {name}!" def add(a: int, b: int) -> int: """Add two numbers.""" return a + b app = expose_tools([greet, add], title="My MCP Tools") Run with: uvicorn server:app --reload MCP endpoints appear at /mcp/list_tools and /mcp/invoke/. TypeScript example: import { z } from 'zod'; import { tool, exposeTools } from 'polymcp'; const uppercaseTool = tool({ name: 'uppercase', description: 'Convert text to uppercase', inputSchema: z.object({ text: z.string() }), function: async ({ text }) => text.toUpperCase(), }); const app = exposeTools([uppercaseTool], { title: "Text Tools" }); app.li
Read the rest
sten(3000); Business example (Python): import pandas as pd from polymcp.polymcp_toolkit import expose_tools def calculate_commissions(sales_data: list[dict]): df = pd.DataFrame(sales_data) df["commission"] = df["sales_amount"] * 0.05 return df.to_dict(orient="records") app = expose_tools([calculate_commissions], title="Business Tools") What you get: • Reuse existing code with minimal changes • Compatible with MCP clients (Claude Desktop, agents, Ollama, etc.) • HTTP and stdio and Wasm support • Automatic validation • Basic production features (budgets, retries, redaction, logs) • Inspector: polymcp inspector for testing/monitoring Install: • Python: pip install polymcp • TypeScript: clone repo → cd polymcp-ts → npm install → npm run build Repo: https://github.com/poly-mcp/Polymcp Curious what kind of function people would expose first if it was this simple. Feedback welcome.
1 points · Open discussion
justvugg·Jan 27, 2026Submission

Show HN: PolyMCP – Expose Python and TypeScript Functions as MCP Tools

I built PolyMCP, a framework that lets you transform any Python or TypeScript function into an MCP (Model Context Protocol) tool ready to be used by AI agents — no rewriting, no complex integrations. Examples Python 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 AI agents can now call add(3, 4) directly. TypeScript function: import { z } from 'zod'; import { tool, exposeToolsHttp } from 'polymcp'; const uppercaseTool = tool({ name: 'uppercase', description: 'Convert text to uppercase', inputSchema: z.object({ text: z.string() }), function: async ({ text }) => text.toUpperCase(), }); const app = exposeToolsHttp([uppercaseTool], { title: "Text Tools"
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}); app.listen(3000); Agents can call uppercase("hello") and get "HELLO" instantly. Business workflow function (Python example): import pandas as pd from polymcp.polymcp_toolkit import expose_tools_http def calculate_commissions(sales_data: list[dict]): 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") Now AI agents can generate reports automatically. Why it matters • Reuse existing code immediately: legacy scripts, internal libraries, APIs. • Automate workflows: AI can orchestrate multiple tools reliably. • Cross-language: expose Python and TypeScript functions on the same MCP server. • Plug-and-play: no custom wrappers or middleware needed. • Built-in reliability: input/output validation and error handling included. PolyMCP makes any Python or TypeScript function immediately usable by AI agents, standardizing integration across enterprise software. Repo: https://github.com/poly-mcp/Polymcp
1 points · Open discussion
justvugg·Jan 26, 2026Submission

Show HN: PolyMCP Skills – Scalable Tool Organization for MCP-Based AI Agents

Hi everyone, I added a skills system to PolyMCP to solve a common issue with MCP servers at scale. When the number of tools grows: • Agents burn tokens loading raw schemas • Tool discovery becomes noisy • Different agents need different subsets of tools • Orchestration logic leaks into prompts Skills are curated, structured sets of MCP tools with documentation. Agents load only the skills they need instead of full tool schemas. Skills are generated by discovering tools from MCP servers and auto-categorizing them. Example: generate skills from a Playwright MCP server: polymcp skills generate --servers "npx @playwright/mcp@latest" HTTP MCP servers: polymcp skills generate \ --servers "http://localhost:8000/mcp" \ --output ./mcp_skills Stdio MCP servers: polymcp skills generate \ --stdio \ --servers "npx -y @playwright/mcp@latest
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" \ --output ./mcp_skills Enable skills in an agent: agent = UnifiedPolyAgent( llm_provider=llm, skills_enabled=True, skills_dir="./mcp_skills", ) Benefits: • Smaller agent context • Scales to large tool sets • Reusable capabilities across agents • Tool access control without prompt changes • Works with HTTP and stdio MCP servers Repo: https://github.com/poly-mcp/Polymcp
1 points · Open discussion

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