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# `skillmcp`

### Turn any folder of agent skills into a live MCP server with one zero-dependency command.

![License](https://img.shields.io/badge/license-MIT-blue.svg) ![Language](https://img.shields.io/badge/language-python-green.svg) ![Status](https://img.shields.io/badge/status-active-success.svg) ![Python](https://img.shields.io/badge/python-3.9%2B-blue) ![MCP](https://img.shields.io/badge/MCP-stdio-orange) ![License](https://img.shields.io/badge/license-MIT-green) ![Tests](https://img.shields.io/badge/tests-pytest-45c985)

<img src="demo.gif" alt="Demo" width="700" />

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## 🎯 Why?

Trending repos show fast-growing agent-skill ecosystems and MCP-powered coding agents, but skills are usually static SKILL.md or JSON folders without a universal local bridge. Existing MCP servers are app-specific or require heavy SDK setup. skillmcp fills the gap with a tiny stdio MCP adapter that discovers, validates, searches, and exposes skill files to Claude, Cursor, or any MCP client.

**Target audience:** AI agent developers, Claude Code/Cursor users, platform teams, and open-source skill authors who want reusable skills exposed to MCP clients without writing a custom server.

## ✨ Features

- ✨ **Recursively discovers SKILL.md, *.skill.md, and skill.json skill files**
- ✨ **Exposes skills_list, skills_get, and skills_search as MCP tools**
- ✨ **Validates skill folders from the CLI with human or JSON output**
- ✨ **Runs as a dependency-free stdio MCP server with resources/read support**

## 🚀 Quick Start

```bash
# Install
pip install skillmcp

# Run
skillmcp --help
```

## 📦 Installation

### From Source

```bash
git clone https://github.com/YOUR_USERNAME/skillmcp.git
cd skillmcp
```

```bash
# Create virtual environment
python -m venv .venv
source .venv/bin/activate  # Windows: .venv\Scripts\activate

# Install in development mode
pip install -e ".[dev]"

# Run tests
pytest -v
```

## 🎬 Demo

The GIF above was recorded using [Charm VHS](https://github.com/charmbracelet/vhs):

```bash
vhs < demo.tape
```

## 📖 Usage

```bash
# Show help
skillmcp --help

# Common usage examples
skillmcp --example
```

## 🏗️ Architecture

```mermaid
graph LR
    A[Input] --> B[Core Engine]
    B --> C[Output]
    B --> D[Plugins]
    D --> E[Extensions]
```

## 🤝 Contributing

Contributions are welcome! Please:

1. Fork the repo
2. Create a feature branch (`git checkout -b feature/amazing-feature`)
3. Commit your changes (`git commit -m 'Add amazing feature'`)
4. Push to the branch (`git push origin feature/amazing-feature`)
5. Open a Pull Request

## 📄 License

MIT © 2026 — See [LICENSE](LICENSE) for details.

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