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This 'Show HN' post introduces PolyMCP Skills, a new tool designed to improve the organization and scalability of tools for AI agents based on the MCP protocol. It addresses issues like token burning and noisy tool discovery by allowing agents to load only necessary, curated skill sets.
AI 生成摘要
這篇「Show HN」文章介紹了 PolyMCP Skills，這是一個旨在改善基於 MCP 協議的 AI Agent 工具組織和可擴展性的新工具。它透過讓 Agent 只載入必要的、經過策劃的技能集，來解決 Token 燃燒和工具發現雜訊等問題。
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"
--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
