Overview

What if your AI systems could think ahead, coordinate tools intelligently, and stay secure - all without breaking the architecture you already trust? ""Navigating Agentic AI"" gives you the blueprint for building scalable, auditable, and highly modular systems using the Model Context Protocol (MCP) - the emerging backbone of multi-agent orchestration and intelligent tooling. Whether you're integrating LLMs with real-time data pipelines, coordinating complex microservices, or preparing for autonomous decision-making in your stack, this book delivers the practical tools, design patterns, and security strategies that high-performance teams are already applying at scale. Inside, you'll uncover: How to structure secure MCP flows with OAuth 2.1, ETDI contracts, and resource indicators Real-world applications from companies like Microsoft, OpenAI, Neo4j, and Anthropic Techniques to balance throughput, traceability, and trust in agentic systems How to design revocable consent, enforce data residency, and handle multi-region failovers Hands-on examples in Python, TypeScript, and Java that you can build on immediately This isn't theory - it's how modern engineering teams are shipping context-aware, protocol-driven systems today. If you're building AI tools, developer platforms, IoT networks, or anything that demands secure orchestration across services, Navigating Agentic AI is your technical guide to what's next. Build smarter agents. Enforce smarter boundaries. Architect for the future.

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