Hands-On AI Agents for the Modern Web. Embrace agentic thinking with LLMs and MCP to craft real-world intelligent web applications

AI is no longer just about generating text. It’s about building autonomous, goal-driven systems that can reason, act, and collaborate. Hands-On AI Agents for the Web is your practical guide to designing and deploying agentic web applications powered by Large Language Models (LLMs). Starting with the fundamentals of agentic thinking and responsible AI, this book walks you through integrating LLMs into real-world web apps. You’ll progressively enhance your systems with tool calling, Retrieval-Augmented Generation (RAG), and advanced reasoning patterns like ReAct, before moving into the design of fully autonomous agents. As you advance, you’ll explore agent architectures, planning systems, orchestration, and multi-agent collaboration, learning how modern frameworks and protocols like Model Context Protocol (MCP) enable scalable, interoperable AI systems. The book emphasizes hands-on learning, with practical examples that demonstrate how to build AI assistants, coordinate multiple agents, and apply proven design patterns, while avoiding common pitfalls. By the end, you’ll have the skills to build production-ready, intelligent web experiences powered by autonomous agents.