
这个寄存器包含了Coursera课程"AI Agents with Model Context Protocol & TypeScript"的代码示例
概览
这个寄存器包含了Coursera课程"AI Agents with Model Context Protocol & TypeScript"的代码示例. - Node.js 18+ - npm - 一个 OpenAI API 密钥(设置在.env文件中) 每个模块都有自己的代码/目录. 要设置任何模块: 模块一是概念入门——没有代码练习. 在每个模块的代码/目录中创建.env文件 :
概述(AI 翻译)
这个寄存器包含了Coursera课程"AI Agents with Model Context Protocol & TypeScript"的代码示例.
□ 先决条件
- 节点.js 18+
- 没有
- OpenAI API 密钥( 设置在 [[T0] 文件)
□ 设置
每个模块都有自己的code/目录. 要设置任何模块:
– – . . .
□ 课程结构和代码映射
QQ单元1:启动AI代理商的示范背景协议
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- 项目 * * * 类型 * * 代码文件 * * |------------. 为什么我们需要模式背景协议? QQ 模式上下文协议和AI问题解决工具QQ视频QQ-QQ MCP允许AI与电脑交流QQ视频-QQ. 爱尔, 我的人工智能工具读取。 校对:Soup
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单元1是概念性介绍——没有代码练习。
– – . . .
& 模式背景协议
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- 项目 * * * * 类型 * * 代码文件 * * * 运行命令 * * * 唵(引)|(二合引)贺. QQ 模式上下文协议:语法,语义,定时 QQ 视频 QQ .
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- 示范背景协议和AI代理 * * 视频 * * * * * * * * MCP服务器是什么? • 视频
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。
AI Agents with Model Context Protocol & TypeScript - Code Examples
This repository contains code examples for the Coursera course “AI Agents with Model Context Protocol & TypeScript.”
Prerequisites
- Node.js 18+
- npm
- An OpenAI API key (set in
.envfile)
Setup
Each module has its own code/ directory. To set up any module:
cd /code
npm install
cp .env.example .env # Then add your OPENAI_API_KEY
Course Structure & Code Mapping
Module 1: Getting Started with Model Context Protocol (MCP) for AI Agents
| Item | Type | Code Files |
|---|---|---|
| Why Do We Need Model Context Protocol? | Video | — |
| Model Context Protocol & AI Problem Solving with Tools | Video | — |
| MCP Allows AI to Communicate with the Computer | Video | — |
| AI @ Work - What My Work with AI Looks Like | Video | — |
| My AI Tools | Reading | — |
| Learning More & Staying Connected | Reading | — |
Module 1 is conceptual introduction — no code exercises.
Module 2: AI Agent Loops & Model Context Protocol
| Item | Type | Code Files | Run Command |
|---|---|---|---|
| Model Context Protocol: Syntax, Semantics, Timing | Video | — | — |
| Model Context Protocol & AI Agents | Video | — | — |
| What is an MCP Server? | Video | — | — |
| Tool Specifications | Video | — | — |
| Building Your First MCP Server | Ungraded Plugin | 01-intro-to-mcp-agents/code/server.ts |
npm run server |
| Building Your First MCP AI Agent | Ungraded Plugin | 01-intro-to-mcp-agents/code/agent.ts``01-intro-to-mcp-agents/code/llm.ts |
npm run agent |
| Agents Talking to Tools vs. Tools with AI | Video | — | — |
Code Location: 01-intro-to-mcp-agents/code/
Key Files:
| Path | Description |
|---|---|
01-intro-to-mcp-agents/code/server.ts |
Basic MCP tool server with list_files and read_file tools |
01-intro-to-mcp-agents/code/agent.ts |
Agent loop implementation (PERCEIVE→DECIDE→ACT→OBSERVE) |
01-intro-to-mcp-agents/code/llm.ts |
LLM integration utilities (OpenAI/Anthropic) |
01-intro-to-mcp-agents/code/test-server.ts |
Tests server tools directly without an agent |
Commands:
cd 01-intro-to-mcp-agents/code
npm install
npm run server # Start the basic MCP server
npm run agent # Run the basic agent
npm run test-server # Test server tools directly
Module 3: Building AI Agents with Model Context Protocol
| Item | Type | Code Files | Run Command |
|---|---|---|---|
| Resources | Video | — | — |
| Teaching Agents to Use Tools | Ungraded Plugin | 01-intro-to-mcp-agents/code/workspace-server.ts |
npm run workspace-server |
| Teaching Agents to Seek Help | Ungraded Plugin | 01-intro-to-mcp-agents/code/workspace-server.ts |
npm run workspace-server |
安装
This server does not publish a one-line install command.
Open the repository installation guide 新手?先看 mcpskill.org 教程 →