MCP Server from Scratch
by KunjShah95
This project demonstrates how to build an MCP (Model Context Protocol) server from scratch using Python. It allows users to connect and interact with the server by handling MCP packets efficiently.
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MCP Server from Scratch using Python
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📜 Description
This repository contains a project for creating an MCP (Model Context Protocol) server from scratch using Python. MCP is used in AIML (Artificial Intelligence Markup Language) to handle context and model interactions. The main objective is to demonstrate how to build a server that can handle MCP packets, allowing users to connect and interact with the server efficiently.
🚀 Features
- 🛠️ Custom MCP (Model Context Protocol) Handling
- 🔄 Packet Parsing and Serialization
- ⚙️ Multiplayer Server Capabilities
- 📝 Detailed Documentation
🛠️ Current Features
- Custom packet handling
- Context management
- Basic model integration
- Communication system
📅 Future Updates
- Advanced context management
- Model training support
- Full command system
- Plugin support
🛠️ Installation
To install and run the server, follow these steps:
- Clone the repository:
git clone https://github.com/KunjShah95/MCP-SERVER-FROM-SCRATCH-USING-PYTHON.git
- Navigate to the project directory:
cd MCP-SERVER-FROM-SCRATCH-USING-PYTHON
- Install the required dependencies:
pip install -r requirements.txt
- Run the server:
python server.py
🤝 Contributing
Contributions are what make the open source community such an amazing place to be learn, inspire, and create. Any contributions you make are greatly appreciated.
- Fork the Project
- Create your Feature Branch (
git checkout -b feature/AmazingFeature
) - Commit your Changes (
git commit -m 'Add some AmazingFeature'
) - Push to the Branch (
git push origin feature/AmazingFeature
) - Open a Pull Request
📄 License
Distributed under the MIT License. See LICENSE
for more information.
📧 Contact
Kunj Shah - @your_username - [email protected]
Project Link: https://github.com/KunjShah95/MCP-SERVER-FROM-SCRATCH-USING-PYTHON
🌟 Acknowledgments
- This project is heavily inspired by the official CLAUDE ANTHROPIC and Model Context Protocol documentation.
- Special thanks to all contributors who have helped improve this project.