Overview

Model Context Protocol (MCP) in AI Agents, 2nd Edition The Ultimate Guide to Building Context-Aware, Integrated, and Intelligent AI Systems If you're building with large language models (LLMs), multi-agent AI systems, or next-gen automation tools like OpenAI Assistants, AutoGen, LangChain, Claude, or CrewAI-this book is your blueprint for context-aware AI development. In this fully updated 2nd Edition, you'll master the Model Context Protocol (MCP)-a breakthrough open standard that bridges LLMs with live, structured external data using clean JSON-RPC calls. Whether you're a developer, ML engineer, system architect, or product builder, this guide shows you how to scale AI agents beyond simple prompts into reliable, interoperable, and real-world-ready tools. What's New in the Second Edition? ✅ Deep coverage of MCP v2.1 (structured context_spec, context_value, validation logic) ✅ New full-stack projects: news summarizer, doc retriever, financial dashboard agents ✅ Native integration patterns with Claude, GPT-4-turbo tools, and OpenAI Assistants v2 ✅ Multi-agent context routing and shared context architectures ✅ Advanced scaling strategies: Docker, Redis, n8n, OpenTelemetry, and load balancing ✅ Security, privacy, and compliant context sharing built-in Inside You'll Learn How To: ✔ Build your own MCP-compliant context servers with FastAPI ✔ Connect agents to live APIs, file systems, databases, and embeddings ✔ Implement stateless, testable context handlers for any agent runtime ✔ Cache, scale, and monitor context pipelines in production ✔ Use MCP in LangGraph, CrewAI, and AutoGen workflows ✔ Future-proof your LLM stack with interoperable agent design Built for real-world engineers, this book includes runnable code, test payloads, curl-ready examples, no-fluff architectural guidance, and GitHub companion resources. Whether you're integrating with GPT, Claude, or rolling your own multi-agent crew, Model Context Protocol (MCP) in AI Agents gives you the tools, patterns, and precision you need to build the next generation of modular, intelligent, context-aware AI systems.

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