MCP Hub Documentation

@reddy-sh

代码仓库主页

基本信息

分类

记忆与知识

许可证

Apache-2.0

传输方式

stdio

作者

reddy-sh

关于 MCP Hub Documentation

MCP Hub is a comprehensive framework for building, managing, and deploying Model Context Protocol (MCP) clients and servers. It provides tools and configurations to enable seamless integration and execution of end-to-end MCP workflows.

#python #mcp #llm#llmapps#mcp-server #modelcontextprotocol #mcp-client

MCP Hub Documentation 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "mcp-hub-reddy-sh": {
      "command": "uv",
      "args": [
        "init"
      ]
    }
  }
}

MCP Hub Documentation 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is MCP Hub Documentation?

MCP Hub Documentation is a framework for creating and managing Model Context Protocol (MCP) servers and clients. It leverages the uv tool for fast package installation and configuration management.

How to use MCP Hub Documentation?

Initialize a project with uv init, set up a virtual environment with uv venv, activate it, then install dependencies using uv add "mcp[cli]" httpx. Create a server file (e.g., XYZ.py) and run it with uv run XYZ.py.

Key features of MCP Hub Documentation

Uses uv for fast package and configuration management.
Provides step‑by‑step instructions to create an MCP server.
Includes sample scripts for image processing, machine learning, and computer vision.
Contains JupyterHub configuration and startup scripts.
Offers a script to download the CIFAR‑10 dataset.
Supports virtual environment setup and dependency locking.

Use cases of MCP Hub Documentation

Creating a new MCP server from scratch.
Running an MCP server for local development or testing.
Leveraging computer‑vision and AI scripts for learning or prototyping.
Setting up a JupyterHub environment for collaborative notebooks.

常见问题

What is the purpose of MCP Hub Documentation?

It is a framework to create and manage MCP servers and clients, providing tools and example code.

Which dependencies are required?

You need `uv`, `mcp[cli]`, and `httpx`. The README also references Python and a virtual environment.

How do I run an MCP server?

After creating the server file, run `uv run XYZ.py`, where `XYZ` is your project name.

What is the role of the `ai/` folder?

It contains subdirectories with scripts for image handling, preprocessing, feature extraction, ML, deep learning, classification, object detection, segmentation, and dataset utilities.

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