AI Agents and Applications

AI-powered applications are rapidly becoming the new normal. Personal productivity assistants, coding agents, smarter search, and automated reporting tools are popping up everywhere. The LangChain ecosystem, and standards like MCP are driving this new gold rush. This book helps you claim your spot. This is your hands-on guide to creating real, production-ready language model solutions. With LangChain and LangGraph, you’ll orchestrate powerful agentic workflows and build dynamic tool-based agents that can search, summarize, reason, and act. You’ll move from essential prompt engineering to advanced Retrieval Augmented Generation (RAG), and finally to deploying multi-agent systems using modern integration standards like the Model Context Protocol (MCP). In AI Agents and Applications: With LangChain, LangGraph and MCP, you’ll discover: • Prompt and context engineering for accurate, hallucination-resistant systems • Advanced RAG for summarization, semantic search, and reliable Q&A • Structured, multi-step agentic workflows with LangGraph • Tool-based agents that adapt in real time • Multi-agent systems for complex, real-world tasks • MCP integration to expose, compose, and consume plug-and-play tools About the technology This book teaches you to design reliable LLM-powered systems by focusing on the concepts, architectures, and design patterns that will stay stable even as models and APIs change. You’ll learn to structure prompts, compose modular chains, and build RAG pipelines that ingest documents, split them into chunks, embed them, retrieve the right context, and ground answers to elliminate (or vastly reduce) hallucinations. About the book Along the way you’ll build concrete applications—summarization and Q&A engines, context-aware chatbots with memory, and tool-using…