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# `mcp-vcr`

### VCR for MCP servers: record and replay AI agent tool calls to test agentic workflows without side-effects or rate limits.

![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) ![PyPI](https://img.shields.io/pypi/v/mcp-vcr) ![License](https://img.shields.io/badge/license-MIT-blue) ![Python](https://img.shields.io/badge/python-3.8+-blue)

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

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## 🎯 Why?

Developers building AI agents with MCP servers struggle to test workflows that trigger side-effects (sending emails, creating tickets) or hit API rate limits during debugging loops. While VCR-style recording exists for HTTP, there is no lightweight, zero-dependency stdio proxy to record and replay JSON-RPC MCP traffic locally.

**Target audience:** AI agent developers, MCP server authors, and QA engineers who need deterministic, offline testing for agentic workflows.

## ✨ Features

- ✨ **Record MCP stdio traffic to a local JSON cassette file**
- ✨ **Replay saved tool calls deterministically without spawning the upstream server**
- ✨ **Zero-dependency, transparent stdio proxy that works with any MCP client (Claude Desktop, Cursor, etc.)**

## 🚀 Quick Start

```bash
# Install
pip install mcp-vcr

# Run
mcp-vcr --help
```

## 📦 Installation

### From Source

```bash
git clone https://github.com/YOUR_USERNAME/mcp-vcr.git
cd mcp-vcr
```

```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
mcp-vcr --help

# Common usage examples
mcp-vcr --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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