README.md

---
title: 🔄 LLM Conversation Transfer Tool
emoji: 🔄
colorFrom: blue
colorTo: purple
sdk: gradio
sdk_version: 5.33.1
python_version: 3.1
app_file: app.py
pinned: false
tags:
- mcp-server-track
- llm
- conversation-transfer
- gradio
- mcp
---

# 🔄 LLM Conversation Transfer Tool

**Tags:** mcp-server-track

A powerful tool that seamlessly transfers conversations between different LLM providers (ChatGPT, Claude, Mistral, etc.) and functions as both a Gradio web app and an MCP (Model Context Protocol) server.

## [Link to the Demo video](https://drive.google.com/file/d/1jHsv4c0yqhA2o0FBhkZOegBrf3A6IVyF/view?usp=sharing)

## 🌟 Features

- **Universal Conversation Parser**: Supports JSON format, plain text, and various chat export formats
- **Multiple LLM Providers**: Transfer to Anthropic Claude, Mistral AI, and Hyperbolic Labs
- **Dual Interface**: Web app for interactive use + MCP server for programmatic access
- **Smart Context Preservation**: Maintains conversation flow and context during transfers
- **Real-time Status**: Live API key validation and connection status

## 🚀 How to Use

### Web Interface
1. **Paste Your Conversation**: Copy from ChatGPT, Claude, or any chat interface
2. **Select Providers**: Choose source and target LLM providers
3. **Transfer**: Click the button and get a response from your target LLM

### As MCP Server
This app can be used as an MCP server with any MCP-compatible client:

**Available Tool:** `transfer_conversation`
- `history_text`: Conversation in JSON or plain text format
- `source_provider`: Source LLM name (ChatGPT, Claude, etc.)
- `target_provider`: Target LLM (anthropic, mistral, hyperbolic)

## 📖 MCP Server Demo Video

[🎥 **Watch the MCP Server in Action**](https://your-demo-video-link-here.com)

*The video demonstrates:*
- Setting up the MCP server with Claude Desktop
- Transferring a conversation from ChatGPT to Claude
- Using the tool within an MCP client environment
- Real-time conversation continuation across different LLMs

## 🔧 Supported Formats

### Input Formats
```
Plain Text:
User: Hello there!
Assistant: Hi! How can I help you?

JSON:
[
  {"role": "user", "content": "Hello there!"},
  {"role": "assistant", "content": "Hi! How can I help you?"}
]
```

### Supported Providers
- ✅ **Anthropic** (Claude 3 Haiku)
- ✅ **Mistral AI** (Mistral Small)
- ✅ **Hyperbolic Labs** (Llama 2)

## 🛠️ Technical Details

Built with:
- **Gradio**: Interactive web interface
- **MCP (Model Context Protocol)**: Server functionality
- **HTTPX**: Async HTTP requests
- **Modal**: Cloud deployment platform

### API Integration
- Anthropic Messages API
- Mistral Chat Completions API  
- Hyperbolic Labs API

## 🚦 Setup & Configuration

### Environment Variables
```env
ANTHROPIC_API_KEY=your_anthropic_key
MISTRAL_API_KEY=your_mistral_key
HYPERBOLIC_API_KEY=your_hyperbolic_key
```

### Local Development
```bash
# Install dependencies
pip install -r requirements.txt

# Run as web app
python main.py

# Run as MCP server
python mcp_server.py
```

### Modal Deployment
```bash
modal deploy main.py
```

## 🎯 Use Cases

- **LLM Comparison**: Test how different models respond to the same conversation
- **Context Migration**: Move conversations between different AI assistants
- **Model Evaluation**: Compare responses across multiple LLM providers
- **Workflow Integration**: Embed in larger AI workflows via MCP protocol

## 📊 Status Dashboard

The app includes real-time status monitoring:
- API key validation
- Connection health checks
- Transfer success rates
- Error reporting

## 🔒 Privacy & Security

- No conversation data is stored
- API keys are handled securely through environment variables
- All transfers happen in real-time without logging
- HTTPS connections for all API calls

## 🤝 Contributing

This project is part of the MCP Server Track. Contributions welcome!

1. Fork the repository
2. Create a feature branch
3. Submit a pull request

## 📜 License

MIT License - feel free to use and modify!

---

**Made for the MCP Server Track** 🏆

*Seamlessly bridging conversations across the AI ecosystem*