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Paperback MCP & AI AGENTS in Action: Build, Deploy, and Scale Context-Aware Agentic AI Systems with MCP, Python, LangChain, LangGraph, and RAG Workflows Book

ISBN: B0G256JXG3

ISBN13: 9798274272957

MCP & AI AGENTS in Action: Build, Deploy, and Scale Context-Aware Agentic AI Systems with MCP, Python, LangChain, LangGraph, and RAG Workflows

Unlock the Power of Context-Aware AI Systems with MCP, Python, LangChain, LangGraph, and RAG Workflows

Master the art of building intelligent, autonomous AI systems that can reason, act, and adapt across multiple tools and data sources. MCP & Agentic AI in Action is your step-by-step guide to designing, deploying, and scaling production-grade agentic AI architectures using the latest techniques in Large Language Models (LLMs).

Written for experienced developers, AI engineers, and data scientists, this book takes you beyond theoretical concepts into real-world implementations. You'll explore how to orchestrate multi-agent systems, manage stateful execution graphs, implement fault-tolerant workflows, and enforce safety constraints-all while maintaining observability, governance, and operational excellence.

Inside this book, you will learn how to:

Design and implement graph-based agent orchestration pipelines using Python, LangChain, and LangGraph.

Apply Multi-Context Protocol (MCP) principles to enable context-aware reasoning and decision-making.

Build robust embeddings pipelines and integrate vector databases such as FAISS, Pinecone, or Weaviate.

Implement verification, human-in-the-loop checks, and fail-safe mechanisms for reliable automation.

Test, monitor, and optimize AI workflows for cost, latency, and accuracy.

Deploy agentic AI systems in containerized, serverless, and managed orchestration environments while ensuring security and compliance.

Through detailed examples, runnable Python code, and expert commentary, you'll gain the knowledge and confidence to operationalize sophisticated agentic AI systems in real-world scenarios-such as automated customer support, research synthesis, and SRE workflow automation.

Whether you're designing a single-agent pipeline or coordinating multiple AI agents in a collaborative environment, this book gives you the tools, patterns, and best practices to succeed.

Step into the future of AI development-build systems that don't just respond, but think, plan, and act intelligently.

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