Autonomous AI with MCP and RAG A Practical Guide to Designing Agentic Systems That Plan, Retrieve, and Reason Unlock the future of artificial intelligence with this definitive guide to building autonomous, reasoning-capable AI systems using Multi-Component Planning (MCP) and Retrieval-Augmented Generation (RAG) . Whether you're a developer, researcher, or AI strategist, this book will transform how you think about and build AI. In an era where prompt engineering is no longer enough, agentic systems offer a leap forward--blending planning, memory, tool use, and retrieval into cohesive, intelligent agents. With clear explanations, real-world architectures, and actionable code patterns, this book walks you through the entire journey from foundational concepts to scalable deployment. Inside, you'll discover: How MCP works as the "brain" behind agentic autonomy--and how it goes far beyond standard RAG pipelines The anatomy of next-gen agents : planners, retrievers, generators, memory modules, and executors Real-world projects : from research assistants and support chatbots to multi-agent task swarms using CrewAI Advanced techniques for minimizing hallucinations, optimizing retrieval fidelity, and orchestrating agent collaboration Blueprints for cloud-native deployment , observability, and performance scaling Ethical considerations , safety mechanisms, and the road from agentic AI toward Artificial General Intelligence (AGI) With appendices full of quick-reference code snippets, tooling indexes, visual blueprints, and a glossary of agentic AI terminology, this book is both a playbook and a field manual for modern AI development. If you're ready to stop prompting and start building autonomous systems that think, plan, and act , Autonomous AI with MCP and RAG is your essential guide.
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