Sign In Start Free Trial
Account

Add to playlist

Create a Playlist

Modal Close icon
You need to login to use this feature.
  • Book Overview & Buying Design Multi-Agent AI Systems Using MCP and A2A
  • Table Of Contents Toc
Design Multi-Agent AI Systems Using MCP and A2A

Design Multi-Agent AI Systems Using MCP and A2A

By : Gigi Sayfan
1 (1)
close
close
Design Multi-Agent AI Systems Using MCP and A2A

Design Multi-Agent AI Systems Using MCP and A2A

1 (1)
By: Gigi Sayfan

Overview of this book

Frustrated by opaque agent frameworks that hide how things work? This book gives you complete control by guiding you through building a fully functional, extensible agentic AI framework in Python without relying on external orchestration tools. You’ll begin by implementing a simple tool-using agent, and then gradually extend its capabilities with structured tool schemas, user interfaces, and memory via the Model Context Protocol (MCP). From there, you’ll build collaborative multi-agent systems powered by Agent-to-Agent (A2A) messaging and deploy them in realistic environments. Along the way, you’ll explore secure tool invocation, message routing, observability, and human-in-the-loop workflows. With annotated code, deep engineering insights, and practical deployment patterns, this hands-on guide equips you to build AI agents that reason, plan, act, and adapt, whether you’re shipping production systems or experimenting with cutting-edge LLM-based architectures. Written by Gigi Sayfan, who builds AI agent infrastructure at Perplexity and is a bestselling author with decades of experience in AI and distributed systems, this book gives you the tools and knowledge to engineer your own advanced agentic systems. *Email sign-up and proof of purchase required
Table of Contents (18 chapters)
close
close
Lock Free Chapter
1
Part 1: Foundations of Agentic AI
5
Part 2: Building Your Own Agentic AI Framework
10
Part 3: Constructing Multi-Agent Systems
17
Index

3

A Hands-On Walk-Through of a Simple AI Agent

In Chapter 2, we explored the foundational concepts of AI agents, their architecture, components, and how they interact with tools and external systems. We also discussed how these principles, such as the agentic loop and memory, are implemented in the popular AutoGen (https://github.com/microsoft/autogen) framework. In this chapter, we will build on that knowledge by dissecting a simple AI agent, k8s-ai, that can interact with a Kubernetes cluster one line at a time. The power of AI agents with tool access will become evident as we walk through the code and understand exactly how an agent loop works. And combining this simple agent with a tool to access Kubernetes will demonstrate how even such a basic setup can be very capable.

We will set the stage by introducing the k8s-ai agent and showcasing its capabilities by running it and interacting with it through a chat interface. Once you have experienced the agentic capabilities...

CONTINUE READING
83
Tech Concepts
36
Programming languages
73
Tech Tools
Icon Unlimited access to the largest independent learning library in tech of over 8,000 expert-authored tech books and videos.
Icon Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.
Icon 50+ new titles added per month and exclusive early access to books as they are being written.
Design Multi-Agent AI Systems Using MCP and A2A
notes
bookmark Notes and Bookmarks search Search in title playlist Add to playlist download Download options font-size Font size

Change the font size

margin-width Margin width

Change margin width

day-mode Day/Sepia/Night Modes

Change background colour

Close icon Search
Country selected

Close icon Your notes and bookmarks

Confirmation

Modal Close icon
claim successful

Buy this book with your credits?

Modal Close icon
Are you sure you want to buy this book with one of your credits?
Close
YES, BUY

Submit Your Feedback

Modal Close icon
Modal Close icon
Modal Close icon