Overview

Model Context Protocols for AI From Prompting to Autonomous Thinking - Build Context-Rich, Memory-Savvy, Ethical AI Agents The secret to building truly intelligent AI isn't just better models-it's better context. What if your AI system could think with purpose, remember with structure, and evolve with awareness? This is not a book about just prompting. It's the blueprint for constructing context-aware AI systems that reason, adapt, and act like never before. Model Context Protocols for AI is your definitive guide to: - Understanding the full lifecycle of context in LLM-driven systems-from ephemeral prompts to persistent memory. - Mastering techniques like zero-shot, few-shot, and prompt engineering-and when to go beyond them. - Building scalable AI memory architectures using vector databases, RAG, Pinecone, ChromaDB, and more. - Implementing real-world frameworks like LangChain, LlamaIndex, and Semantic Kernel to supercharge context management. - Designing autonomous agents with memory, planning, API integration, and multi-hop reasoning. - Creating interoperable and ethical context protocols for multi-agent systems, including handshakes, synchronization, and transparency. What's Inside? - 14 in-depth chapters across 5 parts-from fundamentals to emerging frontiers like self-reflective agents, contextual general intelligence, and industry case studies. - 40+ context protocols and architectural diagrams - Real-world examples from OpenAI, Claude, Microsoft Copilot, and top AI startups - Actionable templates, code snippets, and best practices you can apply immediately Whether you're an AI developer, machine learning engineer, researcher, product manager, or founder, this book will elevate how you build and think about AI. Ready to Build Smarter, Contextual, and Autonomous AI? Don't just fine-tune your models-supercharge your systems. Grab your copy of Model Context Protocols for AI today and join the next generation of AI builder's creating intelligent systems that think, remember, evolve, and adapt.

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