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AI Agents with Model Context Protocol & Typescript
Coursera
Course
Unknown

AI Agents with Model Context Protocol & Typescript

Vanderbilt University

Build AI Agents That Actually Work AI agents are everywhere—but most of them fail in frustrating, unpredictable ways. They get confused, waste tokens, hit dead ends, and require constant babysitting.

Unknown5 weeksArabic, German, English, French

About this Course

Build AI Agents That Actually Work AI agents are everywhere—but most of them fail in frustrating, unpredictable ways. They get confused, waste tokens, hit dead ends, and require constant babysitting. This course teaches you the patterns and architectures that separate agents that struggle from agents that succeed. Using TypeScript and the Model Context Protocol (MCP), you'll learn to build AI agents from the ground up—and more importantly, you'll learn why certain designs work while others fall apart. What You'll Learn: - Build MCP Tool Servers — Create the bridge that lets AI agents interact with any system: filesystems, databases, APIs, or your own custom tools - Master the Agent Loop — Understand the universal pattern every AI agent follows: PERCEIVE → DECIDE → ACT → OBSERVE → REPEAT - Connect agents to tools — Wire up LLMs to discover, select, and execute tools autonomously The Patterns That Make Agents Reliable: - Response-as-Instruction — Your tools don't just return data—they guide agent behavior in real-time. Learn to design tool responses that teach the agent what to do next, when to stop, and how to communicate results. - Failing Forward — Turn errors from dead ends into stepping stones. Design error messages that teach agents how to recover—automatically, without human intervention. For the first time in computing history, your error messages have a reader that can actually do something about them. - Intelligence Budget — Every token in the context window is precious attention. Learn to maximize signal and minimize noise—pre-digesting data in tools, using scripted orchestration for mechanical work, and reserving the agent's cognitive resources for decisions that actually require intelligence

What You'll Learn

  • How to build AI agents with Model Context Protocol and TypeScript
  • How to design self-healing tools that guide agents through errors automatically
  • How to create efficient agents that maximize results while minimizing costs

Prerequisites

  • No deep prior experience is required, but basic computer and internet skills are helpful
  • Ability to read course instructions in English and complete short practice activities

Instructors

D

Dr. Jules White

Professor of Computer Science

Topics

Machine Learning
Data Science
Software Development
Computer Science
Multimodal Prompts
Prompt Patterns
Agentic systems
Model Context Protocol
LLM Application
Prompt Engineering Tools

Course Info

PlatformCoursera
LevelUnknown
PacingUnknown
PriceFree

Skills

بروتوكول سياق النموذج
TypeScript
وكلاء الذكاء الاصطناعي
تصميم الأدوات
معالجة الأخطاء
تحسين الكفاءة
Agentic systems
Model Context Protocol
LLM Application
Prompt Engineering Tools

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