Build a Multi-Agent System with MCP and A2A (From Scratch)

About this book

Build AI agent systems that coordinate, delegate, and get real work done. Agents turn LLMs into autonomous tools capable of executing on tasks and plans. Multi-agent systems use protocols like MCP and A2A to upgrade the power of a single AI agent with a collaborative AI team. In Build A Multi-Agent System (From Scratch) you’ll learn how to construct one of these dynamic, powerful, and effective systems from the ground up. In Build a Multi-Agent System (From Scratch) you will learn how to: • Build a complete LLM agent infrastructure from scratch, including interfaces, tools, data structures, and processing loops • Orchestrate tool calling with LLMs and connect agents to the Model Context Protocol (MCP) ecosystem • Implement human-in-the-loop patterns and add memory modules to share state across tasks • Evaluate agent and multi-agent performance on real tasks • Add Agent2Agent compatibility so multiple agents can collaborate and solve distributed problems Effectively implementing a multi-agent system requires in-depth infrastructure—and that’s exactly what you’ll build in Build A Multi-Agent System (From Scratch)! Instead of relying on frameworks, you’ll design the foundations yourself: the agent loop, tool orchestration, memory, and human-in-the-loop enhancements. Soon, you’ll have an in-depth understanding of how multi-agent systems work because you’ve built your very own! about the reader For software engineers and AI scientists who know Python, and are familiar with working with LLMs. No specialist hardware required—everything in this book should run on a laptop.