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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 built MAKDO, a complete multi-agent system for Kubernetes DevOps. We saw how the Coordinator, Analyzer, Fixer, and Slack_Bot agents work together using MCP and A2A to automate cluster health monitoring and remediation. We implemented the system, connected it to external tools such as k8s-ai and Slack via MCP, and ran it from end to end.
Building multi-agent systems is one thing; keeping them running reliably in production is another. Multi-agent systems fail in unique ways that traditional software doesn’t. Agents hallucinate. They misuse tools. They lose context when handing work between agents. Coordination breaks down. These failures are often non-deterministic and hard to reproduce.
This chapter covers everything you need to test, debug, and troubleshoot multi-agent systems effectively. We start by looking at common failure modes such as hallucination and coordination...