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# `curl2mcp`

### Turn any curl command into a Model Context Protocol tool server in seconds.

![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) ![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg) ![Python](https://img.shields.io/badge/python-3.9%2B-blue.svg) ![MCP](https://img.shields.io/badge/MCP-compatible-8a2be2.svg)

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

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## 🎯 Why?

MCP adoption is exploding, but connecting a random REST endpoint still means writing a server, schema, and request glue. curl is the universal language for HTTP requests, yet there is no tiny zero-config adapter that converts a curl command into an MCP tool. curl2mcp fills that gap by parsing {placeholders} and serving the request over stdio.

**Target audience:** AI tool builders, Claude/Cursor users, platform engineers, and agent developers who need to expose HTTP APIs to MCP clients without writing boilerplate.

## ✨ Features

- ✨ **Parse a curl command into an MCP tool schema with placeholder extraction**
- ✨ **Run the templated request directly from the CLI for quick testing**
- ✨ **Serve the tool over MCP stdio for Claude, Cursor, or any MCP client**
- ✨ **Zero external runtime dependencies beyond the Python standard library**

## 🚀 Quick Start

```bash
# Install
pip install curl2mcp

# Run
curl2mcp --help
```

## 📦 Installation

### From Source

```bash
git clone https://github.com/YOUR_USERNAME/curl2mcp.git
cd curl2mcp
```

```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
curl2mcp --help

# Common usage examples
curl2mcp --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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