欢迎使用MCP Lab, 集项目,演示,以及使用模型背景协议(MCP)的实验. 该寄存器作为一个游乐场,探索MCP在将AI模型与外部工具,数据源和服务连接起来时的功率和多功能.

将 MCP 视为 AI ** 的 ** USB- C – 这是将大型语言模型(LLMs)用最小自定义代码插入您工具的标准化方法.

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结构

此 repo 中的每个文件夹都代表一个独立,自成一体的项目或使用 MCP 构建的教程. 项目从方便初学者的坠机课程到更深入地融入现实世界的API和当地基础设施不等.

每个项目包括:

• 明确的设置指令
• MCP服务器和/或客户的源代码
• 实例或录像
• 可选Claude或地方LLM整合

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为什么是MCP?

示范环境协议使:

• ** 有限责任公司和外部工具之间的组合
• ** 了解本地第一设计**(无需将数据暴露在云中)
• ** 可用于Slack、GitHub、数据库和其他的可操作、可重复使用的服务器**
• LLM-不可知论建筑(与克洛德,奥拉马,ChatGPT等合作)

🧪 MCP Lab – Experiments with Anthropic’s Model Context Protocol

Welcome to MCP Lab, a collection of projects, demos, and experiments using Model Context Protocol (MCP). This repository serves as a playground to explore the power and versatility of MCP in connecting AI models to external tools, data sources, and services.

Think of MCP as USB-C for AI – a standardized way to plug large language models (LLMs) into your tools with minimal custom code.

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📂 Structure

Each folder in this repo represents an independent, self-contained project or tutorial built using MCP. Projects vary from beginner-friendly crash courses to deeper integrations with real-world APIs and local infrastructure.

mcp-lab/
│
├── mcp-crash-course/         # Introductory project – walk-through of MCP basics
├── Coming soon...

Each project includes:

• Clear setup instructions
• Source code for MCP servers and/or clients
• Examples or video walkthroughs
• Optional Claude or local LLM integration

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🧠 Why MCP?

Model Context Protocol (MCP) enables:

• 🔌 Plug-and-play integrations between LLMs and external tools
• 🔒 Privacy-aware, local-first design (no need to expose your data to the cloud)
• 🧱 Composable, reusable servers for Slack, GitHub, databases, and more
• 🌐 LLM-agnostic architecture (works with Claude, Ollama, ChatGPT, etc.)

With MCP, you write a connector once, and any compatible model can use it. It’s the future of LLM-to-tool communication.

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🛠 Getting Started

To run any project:

1. Clone the repo:

   git clone https://github.com/Farzad-R/mcp-lab.git
   cd mcp-lab
   

2. Navigate to the project folder you’re interested in (e.g. mcp-crash-course)

3. Follow the README.md inside that folder for setup and instructions

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🎥 Related Video Series

All of these projects are featured in my educational videos on YouTube.

➡️ Watch the full crash course: [MCP Crash Course – YouTube Link]

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🤝 Contributing

Want to add your own MCP experiment?
PRs are welcome! Follow the format of existing folders and include:

• A clear README.md
• A self-contained demo (scripts, server, or configs)
• Optional: video or blog post link

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MCP-Crash-Course YouTube Video: URL

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