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Book Overview & Buying
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Table Of Contents
Design Multi-Agent AI Systems Using MCP and A2A
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In the previous chapter, we explored the backend architecture of the AI-6 framework in detail, focusing on how the engine orchestrates the agentic loop, manages memory and session tate, and integrates with multiple LLM providers and tools. We saw how tools and models are dynamically discovered and how the engine handles their coordination through a unified abstraction. This foundation enables flexible, provider-agnostic AI workflows with persistent memory, resumable sessions, and secure, extensible tool usage.
In this chapter, we will shift focus from the overall engine architecture to a deeper investigation of the tool system itself. While Chapter 4 treated tools largely as pluggable black boxes, here we will look inside and examine how generic tools are designed to be reusable, consistent, and portable across LLM providers. We will explore how tools can be defined with structured schemas, how arguments are validated, and how they are registered...