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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