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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 ventured beyond theory and observed an AI agent in action, specifically controlling a real Kubernetes cluster with a mix of autonomy, reasoning, and tooling. Through the concise yet powerful k8s-ai agent (https://github.com/the-gigi/k8s-ai), we demonstrated foundational AI agent capabilities such as observation, diagnosis, tool usage, maintaining a human-in-the-loop interaction, and employing an agentic loop. This agent, developed in just 61 lines of Python, is an impressive demonstration of the power of AI agents and LLMs.
In this chapter, we will start to develop a more complex and full-fledged AI framework called AI-6 (https://github.com/Sayfan-AI/AI-6/tree/v0.8.0). AI-6 will allow us to explore the full spectrum of AI agent capabilities, such as sophisticated memory management, advanced tool management facilities, and support for multiple LLM providers. AI-6 is highly unopinionated and highly extensible...