Publisher's Synopsis
Autonomous AI with MCP and RAG: Principles, Architecture, and Building Blocks
Unlock the future of AI systems with Autonomous AI with MCP and RAG-a practical, hands-on guide for developers, engineers, and AI architects who want to design intelligent agents using cutting-edge technologies like Model-Context-Protocol (MCP) frameworks and Retrieval-Augmented Generation (RAG).
This book is your complete blueprint for building real-world AI agents that think, plan, and act independently. Learn how to architect and deploy agentic systems using LangChain, OpenAI, AutoGen, CrewAI, ChromaDB, and LlamaIndex. Whether you're developing advanced LLM-based assistants, RAG-enhanced search agents, or collaborative multi-agent workflows, this guide offers clear explanations, code-rich examples, and step-by-step tutorials aligned with 2025's most current practices.
What You'll Learn:
The fundamentals of autonomous agents and multi-agent systems
How to design core agent loops with LangChain and OpenAI
Integrating RAG with vector databases like ChromaDB and Weaviate
Building and deploying FastAPI-based agent backends using Docker
Applying ethical, auditable, and secure practices for AI operations
Real-world architecture diagrams, templates, and deployment patterns
Whether you're a machine learning engineer, Python developer, startup builder, or enterprise architect, this book equips you with the tools and knowledge to create scalable, explainable, and production-ready AI systems.
