Generate MCP servers from plain-English skill descriptions
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# skill-to-mcp > **Turn a plain-English skill description into a working MCP server in seconds.** [](https://www.python.org/) [](LICENSE) [](tests/) [](https://pypi.org/project/skillmd-to-mcp/) [](https://pypi.org/project/skillmd-to-mcp/) [](https://pypi.org/project/skillmd-to-mcp/) [](tests/)  **`skill-to-mcp`** is a CLI code generator that reads a `SKILL.md` file — a plain-English description of a tool — and scaffolds a complete, runnable **MCP (Model Context Protocol) server** with: - ✅ Correct JSON-RPC schema (`tool_name`, `description`, `inputSchema`, `outputSchema`) - ✅ Pydantic v2 models for type-safe input/output - ✅ MCP server boilerplate (stdio or HTTP SSE transport) - ✅ `pyproject.toml` ready for `pip install` - ✅ Auto-generated `README.md` with usage instructions > 📖 [Leggi in Italiano](README.it.md) --- ## Why? Describing a tool in Markdown is **more readable, versionable, and composable** than hand-writing JSON-RPC schemas. `skill-to-mcp` bridges the gap between *"I know what my tool does"* and *"I have a working MCP server."* Read the full motivation: [SKILL.md might be a better abstraction than function calling](https://reddit.com/r/ClaudeAI/comments/1ug83x6/why_skillmd_might_be_a_better_abstraction_than/) --- ## Apify Actor Run skill-to-mcp on the [Apify platform](https://apify.com/): ```bash docker build -t skill-to-mcp . docker run -e DEEPSEEK_API_KEY=sk-... skill-to-mcp ``` The Apify Actor accepts the same inputs as the CLI via a web form: **…
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