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所在平台: Udemy |
课程主页: https://www.udemy.com/course/mastering-model-context-protocol-mcp-a-practical-guide/
课程评论：没有评论
课程名称：掌握模型上下文协议（MCP）：实用指南 概述：掌握模型上下文协议（MCP）是一本实用指南，旨在帮助您利用FastMCP生态系统构建健壮、安全且适合生产的AI后端。此课程将引导您完成每一个步骤，从启动一个基本的MCP服务器到部署一个整合LangGraph、FastAPI和OAuth 2.1安全性的全栈应用程序。您将学习如何设计模块化、可扩展的系统，通过现代协议和最佳实践为大型语言模型（LLM）提供高质量的上下文。课程以实践开发为重点，帮助您构建可扩展的MCP驱动的应用程序，为实际应用做好准备。 课程亮点： - MCP基础知识：设置一个基本的FastMCP服务器和客户端，理解JSON-RPC请求/响应循环并有效处理错误。 - 传输方法：学习如何使用SSE、可流式http（无状态与有状态）和标准输入输出，掌握在不同场景中切换传输的方法。 - 高级MCP功能：实现工具、资源、提示、发现、根和抽样等关键特性，创建动态和自适应的上下文管道。 - LangGraph集成：构建一个与MCP服务器交互并生成智能人类般响应的LangGraph客户端，使用有状态逻辑。 - OAuth 2.1安全性：使用Auth0和OAuth 2.1保护您的端点，应用范围、令牌管理和安全部署的最佳实践。 - FastAPI与代理模式：将MCP嵌入FastAPI中，构建服务的模块化，创建代理桥接以支持遗留系统或替代传输。 - 全栈部署（顶点项目）：将前端、API、MCP服务器和LLM后端的所有组件组合成一个容器化、适合生产的解决方案。 课程结束时，您不仅会理解MCP的理论基础，还将掌握在现代AI工作流中构建、安全和部署MCP的技能。无论您是探索LLM基础设施的开发者，还是构建上下文感知系统的工程师，此课程都为您提供了将AI应用提升到新水平的实用工具。让我们一起构建下一代智能、上下文驱动的系统！
Mastering Model Context Protocol (MCP) is your practical guide to building robust, secure, and production-ready AI backends using the FastMCP ecosystem.This course walks you through every step-from spinning up a minimal MCP server to deploying a full-stack application that integrates LangGraph, FastAPI, and OAuth 2.1 security.You'll learn how to design modular, extensible systems that provide high-quality context to LLMs through modern protocols and best practices. With a strong focus on hands-on development, this course prepares you to build scalable MCP-powered applications that are ready for real-world use.Course HighlightsMCP FundamentalsSet up a basic FastMCP server and client. Understand the JSON-RPC request/response cycle and handle errors effectively.Transport MethodsWork with SSE, streamable-http (stateless & stateful), and stdio. Learn how to switch between transports and apply them in different scenarios.Advanced MCP FeaturesImplement key features like Tools, Resources, Prompts, Discovery, Roots, and Sampling to create dynamic and adaptive context pipelines.LangGraph IntegrationBuild a LangGraph client that interacts with your MCP server and generates intelligent, human-like responses using stateful logic.Security with OAuth 2.1Secure your endpoints using Auth0 and OAuth 2.1. Apply scopes, token management, and best practices for safe deployments.FastAPI & Proxy PatternsEmbed MCP into FastAPI, compose services for modularity, and create proxy bridges to support legacy systems or alternate transports.Full-Stack Deployment (Capstone)Combine all components-frontend, API, MCP server, and LLM backend-into a Dockerized, production-ready solution.By the end of this course, you'll not only understand the theory behind MCP but also have the skills to build, secure, and deploy it in modern AI workflows.Whether you're a developer exploring LLM infrastructure or an engineer building context-aware systems, this course gives you the practical tools to take your AI applications to the next level.Let's build the next generation of intelligent, context-driven systems:-)
