
这是一门全面且注重实践的课程,涵盖从创建第一台MCP服务器到使用Docker和云原生架构部署生产准备应用的一切。
概览
这是一门全面且注重实践的课程,涵盖从创建第一台MCP服务器到使用Docker和云原生架构部署生产准备应用的一切。 - 观看完整教程 : https://youtu.be/io02ZM0ADqM?si=q612y-5459BjTT5j 是一种标准化协议,实现了AI模型与外部工具/系统之间的无缝通信。它允许: - 🔌 :将AI模型连接到自定义工具和服务 - 🌐 :标准化的大型语言模型与资源交互方式 - 🔄 :使用标准、HTTP或自定义传输 - 🛡️ :全类型支持与验证 - 📡 :在远程服务器上执行工具 本大师课将带您完整体验MCP开发过程: 无论你是人工智能爱好者、开发者还是DevOps工程师,这门课程都能满足你的需求!
概述(AI 翻译)
这是一门全面的实践课程,教你关于**模型上下文协议(MCP)**的一切——从创建你的第一台MCP服务器到使用Docker和云原生架构部署生产准备应用。
📚 目录
- 什么是MCP?
- 课程概述
- 先决条件
- 入门指南
- 课程结构
- 项目架构
- 主要特征
- 技术
- 快速入门指南
- 运行示例
- 常见问题解答
- 资源
🤖 什么是MCP?
模型上下文协议(MCP) 是一种标准化协议,能够实现 AI 模型与外部工具/系统之间的无缝通信。它允许:
- 🔌 工具集成:将AI模型与自定义工具和服务连接起来
- 🌐 通用通信:大型语言模型与资源交互的标准化方式
- 🔄 多传输支持:使用stdio、HTTP或自定义传输
- 🛡️ 类型安全:完整的类型支持与验证
- 📡 远程执行:远程服务器上的执行工具
📖 课程概述
本大师课将带您完整体验MCP开发过程:
本页由 AI 翻译,技术细节请以原文为准。
README
以下为原文 README 节选,完整内容请查看原文。
MCP Masterclass - Complete Guide For Beginners
A comprehensive, hands-on course that teaches you everything about Model Context Protocol (MCP) - from creating your first MCP server to deploying production-ready applications using Docker and cloud-native architectures.
- Watch The Full Tutorial : https://youtu.be/io02ZM0ADqM?si=q612y-5459BjTT5j
📚 Table of Contents
- What is MCP?
- Course Overview
- Prerequisites
- Getting Started
- Course Structure
- Project Architecture
- Key Features
- Technologies
- Quick Start Guide
- Running Examples
- FAQ
- Resources
🤖 What is MCP?
Model Context Protocol (MCP) is a standardized protocol that enables seamless communication between AI models and external tools/systems. It allows:
- 🔌 Tool Integration: Connect AI models to custom tools and services
- 🌐 Universal Communication: Standardized way for LLMs to interact with resources
- 🔄 Multi-Transport Support: Use stdio, HTTP, or custom transports
- 🛡️ Type-Safe: Full type support and validation
- 📡 Remote Execution: Execute tools on remote servers
📖 Course Overview
This masterclass takes you on a complete journey through MCP development:
Beginner ─→ Intermediate ─→ Advanced ─→ Production
↓ ↓ ↓ ↓
CH-1 CH-2,3 CH-4,5 CH-6
Whether you’re an AI enthusiast, developer, or DevOps engineer, this course has something for you!
✅ Prerequisites
- Python 3.12+ (MCP requires modern Python)
- Git for version control
- Docker (for Chapter 6)
- Basic Python knowledge (async/await, decorators)
- API familiarity (helpful for understanding HTTP transport)
- Terminal/Command Line comfort
🎯 Getting Started
1. Clone the Repository
git clone https://github.com/yourusername/MCP_Masterclass.git
cd MCP_Masterclass
2. Set Up Python Environment
Using uv (recommended - faster than pip):
uv venv .venv
source .venv/bin/activate # On Windows: .venv\Scripts\activate
Or using traditional venv:
python -m venv .venv
source .venv/bin/activate # On Windows: .venv\Scripts\activate
3. Install Dependencies
uv pip install -r pyproject.toml
# or
pip install -e .
The project includes:
fastmcp- FastMCP framework for building MCP serverslangchain- For integration with language modelslangchain-mcp-adapters- Bridge between LangChain and MCPmcp- Official MCP specification implementationagentic-terminal- Terminal-based MCP tools
4. Verify Installation
python main.py
# Expected output: "Hello from mcp-masterclass!"
安装
docker run -p 8050:8050 mcp-masterclass