Mastering Google Agent-to-Agent (A2A): Building Autonomous Multi-Agent AI Systems to Architect Scalable AI Workflows What if your AI systems could talk to each other like intelligent collaborators—passing tasks, sharing context, adapting in real time, and scaling without breaking down? That’s the promise of Google’s Agent-to-Agent (A2A) protocol, and this book shows you exactly how to harness it. Mastering Google Agent-to-Agent (A2A) is a hands-on developer’s guide for building intelligent multi-agent systems using Google’s Agent Development Kit (ADK), the Model Context Protocol (MCP), and Gemini-powered workflows. Whether you're orchestrating autonomous agents with Autogen, designing agentic systems in Python, or deploying next-gen AI pipelines using JSON-RPC and REST, this book gives you the practical tools and examples you need—fast. You’ll learn to architect scalable AI workflows from the ground up, define robust MCP context envelopes, structure real-world agent communications using the Google ADK Agent Architecture, and deploy action-based, context-aware agents across hybrid cloud environments. This book includes step-by-step guidance on creating end-to-end AI agent pipelines, implementing Python examples for A2A and JSON-RPC endpoints, and using Gemini models in decision agents and tool-using frameworks. What makes this book different? It’s structured for builders. Each chapter delivers focused lessons: Chapter 3: Creating Your First A2A Agent – Walks you through Python implementation and schema definition. - Chapter 4: Context Management with MCP – Shows how to pass memory, goals, and persona across agent chains. - Chapter 5: Secure Authentication – Covers OAuth2, role-based access, and credential strategies in multi-tenant setups. - Chapter 6: Observability – Teaches distributed tracing, SLA monitoring, and structured logging. - Chapter 7: Human-in-the-Loop Checkpoints – Adds approval UIs and auditability to your pipelines. - Chapter 10: Real-World Use Case – Automate reports with n8n and A2A agents in a complete enterprise pipeline. Are you designing AI systems that need to scale without becoming unmanageable? Do you need to coordinate multiple LLM-based agents in production? This book gives you the architecture, the tools, and the confidence to do it right. Take your multi-agent AI development to the next level. Start building autonomous systems that communicate, adapt, and scale—efficiently, reliably, and with real-world impact. Buy the book now and start engineering intelligent pipelines with precision.