Artificial Intelligence has evolved beyond simple model queries - it now depends on context. Every AI response, decision, and recommendation is shaped by the information it can recall, interpret, and maintain. Yet, until recently, context handling was fragmented, inconsistent, and inefficient across systems. Enter the Model Context Protocol (MCP) - a transformative framework that standardizes how AI systems understand, share, and synchronize context across models and environments. MCP represents a major leap toward intelligent, multi-agent collaboration and persistent contextual reasoning - the backbone of modern agentic AI systems. This book serves as your complete roadmap to mastering MCP - from its fundamental concepts to hands-on implementation within advanced AI ecosystems like LangChain, LlamaIndex, and OpenAI's Assistant API. You'll discover how to integrate MCP into your workflows, optimize context windows, and engineer systems that think, remember, and evolve dynamically. By the end, you'll not only understand how MCP works, but also how to use it to power next-generation autonomous AI systems with unmatched precision and scalability.
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