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所在平台: Udemy |
课程主页: https://www.udemy.com/course/modelcontextprotocol/
课程评论：没有评论
课程名称：MCP与A2A - 模型上下文协议与代理到代理协议 课程概述：本课程新增了A2A（代理到代理协议）的组件、生命周期和代码实现。您将学习如何通过A2A连接三个代理，并掌握A2A Python SDK。在本课程中，您将学习MCP（模型上下文协议）和A2A的基础知识，并从零开始构建5个MCP客户端和3个MCP服务器。您将使用Python的Streamlit为MCP客户端构建用户界面，并学习如何使用服务器发送事件在Google Cloud上部署MCP服务器。此外，课程中您将使用Google提供的免费Gemini API密钥，从而在学习过程中无需支付AI模型费用。最终，我们将构建A2A代理、客户端和服务器，并使用Google的代理开发工具包（ADK），将MCP与A2A进行整合。 课程主要目标： - 构建基于Google ADK的A2A服务器、客户端和代理（处于Beta阶段） - 通过A2A连接3个代理，完成全代码实现 - 构建一个主协调代理，并与A2A和MCP集成 - 使用A2A Python SDK - 开发5个MCP客户端，其中包括基本Python与Gemini的集成、基于LangGraph的客户端等 - 创建3个MCP服务器，包括Python STDIO基础服务器和服务器发送事件（SSE）服务器 - 将您的服务器连接到Claude Desktop - 在Google Cloud平台上部署MCP服务器 - 为MCP客户端在Python中构建Streamlit用户界面 - 利用免费的Gemini API密钥避免AI成本 课程详细描述： 在本实用课程中，您将扎实掌握模型上下文协议（MCP）及其双向客户端-服务器架构。我们首先探索MCP的基础知识，帮助您建立信心，能够自信地使用该强大的协议。随后，您将实现自己的MCP服务器，使用Python在MacBook上托管，并与Claude Desktop连接，展示如何与外部工具交互。课程还将引导您开发自己基于Python的MCP客户端，并与Google的Gemini API进行集成。 课程结束时，您将能够： - 理解MCP的基本架构和流程 - 使用Python构建和运行MCP服务器 - 将您的自定义MCP服务器连接到Claude Desktop - 获取和配置免费的Google Gemini API密钥 - 开发基于Google Gemini的自定义Python MCP客户端 - 测试客户端与服务器之间的交互，以运行实际命令 注意事项： 本课程主要关注工具调用，而不涵盖高级MCP原语内容。课程演示使用MacBook进行，Windows用户可根据需要进行参考。课程使用第三方公司和开源项目提供的工具、API和服务，学习者需自行了解和同意相关条款。 免责声明： 本课程信息仅供教育目的，学习者在使用Google账号、Google Cloud平台项目、Gemini API密钥或其他第三方账号和服务时，需自行负责审查相关条款和政策。课程提供者和相关方不对任何第三方服务的准确性、完整性或适用性提供保证。课程不负责因使用这些服务而产生的任何损失或后果。请务必在参与第三方平台或优惠前，独立进行判断和尽职调查。
New - A2A or Agent2Agent Protocol components, lifecycle and code implementations added. Connect 3 Agents via A2A. Learn the A2A Python SDKTLDR - In this course, you'll learn about MCP & A2A - Model Context Protocol & Agent2Agent Protocol. We will build 5 MCP Clients and 3 MCP Servers from Scratch. You'll build a UI for MCP client in Streamlit in Python. You'll learn to deploy your MCP Server to Google Cloud using Server Sent Events. To top it all, we'll use a free Gemini API Key from Google so you don't need to pay for AI Models when learning! We then build A2A Agents, Clients and Servers and use Google's ADK or Agent Development Kit. Integrate MCP + A2A togetherKey Objectives of CourseBuild A2A Servers, Clients and Agents (using Google's ADK or agent development kit) - in BetaConnect 3 Agents via A2A with full code implementationBuild a Host Orchestrator agent - integrate with A2A + MCPA2A Python SDKBuild 5 MCP Clients: #1. Basic Python + Gemini #2. LangGraph Based #3. LangGraph (with config.json) #4. Server Sent Events (SSE)#5. Streamlit MCP ClientBuild 3 MCP Servers: #1 Python STDIO based #2 Python STDIO (with Docker) #3 Server Sent Event (SSE) ServerConnect your server to Claude DesktopDeploy MCP Server on Google Cloud Platform. Yes, you heard that right:)Build Streamlit UI for MCP Client in PythonAvoid AI Costs using a free Gemini API Key: to work with Gemini API, Tools and Function callingDetailed Course DescriptionLearn basics of MCPIn this hands-on course, you will gain a solid foundation in the Model Context Protocol (MCP) and its bidirectional client-server architecture. We begin by exploring the fundamentals of MCP, equipping you with the conceptual understanding needed to work confidently with this powerful protocol.Next, you will implement your own MCP server in Python, hosted on a MacBook. This server will be connected to Claude Desktop, showcasing how you can interact with external tools. As part of this quick start, you'll build and test a tool that executes terminal commands via MCP using Claude Desktop.Building on this foundation, we'll guide you through developing your own MCP client in Python, integrating it with Google's Gemini API. With a free Gemini API Key from Google, you'll connect your client to your MCP server and perform tool invocations just like Claude Desktop.By the end of this course, you will:Understand the basic architecture and flow of MCPLearn to build and run an MCP server using PythonConnect your custom MCP server to Claude DesktopObtain and configure a free Google Gemini API KeyDevelop your own Python-based MCP client powered by Google GeminiTest the interaction between your client and server to run real commandsWhat This Course Does Not Cover:Advanced MCP primitives beyond tool-calling (for now, we focus only on tool invocation)Windows-specific setup: While many steps are applicable across platforms, this course uses a MacBook for demonstrations. Windows users may follow along at their discretion.Important Notes:This course uses tools, APIs, Keys and services provided by third-party companies and open source projects. We do not offer any warranties or guarantees related to these services. Learners are responsible for understanding and agreeing to the terms and policies of each provider.While many resources exist in fragments across the web, this course brings everything together in a streamlined, tested, and learner-friendly format based on real-world implementations.DisclaimerThe information provided in this course is for educational purposes only.Please be advised that when creating a Google account, Google Cloud Platform (GCP) project, using the Gemini API Key or using any other third-party account or service, you are solely responsible for reviewing and understanding the applicable terms and conditions, privacy policies, pricing, usage limits, and any other relevant policies or charges associated with that service.The instructor, course provider, and any affiliated parties do not provide any guarantees, warranties, or representations regarding the accuracy, completeness, or current applicability of any third-party services mentioned in this course, including but not limited to Google Cloud's $300 credit offer and the free Gemini API Key. Policies and offerings may change at any time without notice, and the information in this course may become outdated.By proceeding to create and use any such account or service, you agree that you do so at your own discretion and risk. The instructor and related parties shall not be held liable for any losses, charges, damages, liabilities, or consequences arising from your use or attempted use of such services.Always exercise independent judgment and due diligence before engaging with any third-party platform or offer. The credits and key from Google are available from Google irrespective of whether you take this course or not. We use them to help students setup and learn about MCP and AI without incurring cloud/AI costs.Whether you're a developer, tinkerer, or AI enthusiast, this course will empower you to build practical systems using cutting-edge AI and modern protocol design.
