Design Multi-Agent AI Systems Using MCP and A2A: Engineer your own Python-based agentic AI framework with tool use, memory, and multi-agent workflows
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Design Multi-Agent AI Systems Using MCP and A2A: Engineer your own Python-based agentic AI framework with tool use, memory, and multi-agent workflows
Engineer your own Python-based agentic AI framework with tool use memory and multi-agent workflows.
Design Multi-Agent AI Systems Using MCP and A2A: Engineer your own Python-based agentic AI framework with tool use, memory, and multi-agent workflows
ապրանք#: 242970796

Design Multi-Agent AI Systems Using MCP and A2A: Engineer your own Python-based agentic AI framework with tool use, memory, and multi-agent workflows

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ապրանք#: 242970796

AMD 36549

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Engineer your own Python-based agentic AI framework with tool use memory and multi-agent workflows.
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What Stands Out

Customizable Framework
Build tailored multi-agent AI systems using a Python-based framework that allows for extensive customization and flexibility, addressing specific project requirements efficiently.
Tool Utilization
Incorporate advanced tool use capabilities that enhance agent functionality, enabling complex tasks and interactions that set this framework apart from traditional AI systems.
Memory Integration
Utilize integrated memory systems that improve learning and decision-making for agents, ensuring more intelligent and responsive interactions across collaborative multi-agent environments.

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Shop Design Multi-Agent AI Systems Using MCP and A2A: Engineer your own Python-based agentic AI framework with tool use, memory, and multi-agent workflows online at a best price in Armenia. 1806116472
  • Build a production-ready multi-agent AI framework from scratch using MCP and A2A to orchestrate powerful agent workflowsFree with your book: DRM-free PDF version + access to Packt's next-gen Reader*Key FeaturesBuild Python-based AI agents without relying on third-party orchestration frameworksDesign production-ready multi-agent systems using A2A messagingIntegrate memory and context with MCP to create adaptive and stateful agentic AI frameworksBook DescriptionFrustrated 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 requiredWhat you will learnDesign and implement tool-using AI agents from the ground upBuild modular components for extensible agent frameworksCreate secure and observable tools with structured inputsIntegrate agents with chat UIs such as Slack and ChainlitLeverage MCP for context handling and agent memoryOrchestrate collaborative agent workflows using A2ADebug and deploy agents in production-like environmentsExplore future-ready agent capabilities and GenUX designWho this book is forThis book is essential for AI engineers, ML practitioners, and software architects building agentic systems with large language models. It’s also ideal for DevOps engineers and technical leaders seeking deep insights into building and scaling autonomous AI workflows. Python coding skills and basic familiarity with LLMs are recommended.Table of ContentsIntroduction to Generative AI and AI agentsUnderstanding How AI Agents WorkA Hands on Walk-Through of a Simple AI AgentBuilding a Tool-Based Agentic AI FrameworkImplementing Custom ToolsCreating Chat Interfaces Using Slack and ChainlitIntegrating with the Model Context Protocol EcosystemDesigning Multi-Agent SystemsImplementing Multi-Agent Systems with A2ATesting, Debugging, and Troubleshooting Multi-Agent SystemsDeploying Multi- Agent SystemsAdvanced Topics and Future Directions
Publisher Packt Publishing
Publication date 27 Feb. 2026
Language English
Print length 536 pages
ISBN-10 1806116472
ISBN-13 978-1806116478
Item weight 912 g
Dimensions 19.05 x 3.07 x 23.5 cm

Who Should Buy?

Suitable For
  • AI Developers

    Developers looking to create complex multi-agent systems in Python will find this framework extremely beneficial and efficient.

  • Research Scientists

    Researchers studying distributed systems or multi-agent collaboration will gain significant insights and practical tools from this product.

  • Students in AI

    Students aiming to learn about multi-agent AI systems can engage deeply with the practical applications and coding exercises.

Not Suitable For
  • Beginners in Programming

    Complete beginners might struggle with the complexity and technical requirements needed to effectively utilize this AI framework.

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  • Հարց: What programming language is required for this book?

    Պատասխան: Python coding skills are required.
  • Հարց: Who is this book intended for?

    Պատասխան: It is designed for AI engineers, ML practitioners, software architects, and DevOps engineers.
  • Հարց: Does the book include any free resources?

    Պատասխան: Yes, it includes a DRM-free PDF version and access to Packt’s next-gen Reader.

Introduction to Programming Editorial Review

Design Multi-Agent AI Systems Using MCP And A2A is a comprehensive guide for engineering your own Python-based agentic AI framework that incorporates tool use, memory, and multi-agent workflows. Published by Packt Publishing, this book delves into the intricacies of constructing robust multi-agent systems. With a substantial print length of 536 pages, it offers detailed insights and practices for both beginners and seasoned developers. Readers will appreciate the structured approach, allowing easy navigation through topics relevant to multi-agent frameworks. Its clear language ensures that complex concepts are accessible, making it a valuable resource for anyone interested in artificial intelligence.

Customer Reviews & Ratings

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Կողմ

  • In-depth guide on multi-agent systems
  • Detailed discussions on agentic frameworks
  • Accessible for beginners and experienced developers
  • Well-structured approach for easy navigation
  • Includes practical examples and insights

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  • Publication date is in the future, 2026

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Հատկություններ և առավելություններ

  • Build a production-ready multi-agent AI framework from scratch.
  • Create Python-based AI agents without external orchestration tools.
  • Design adaptive systems using A2A messaging for collaboration.
  • Integrate memory and context with the Model Context Protocol (MCP).
  • Gain hands-on experience with annotated code and practical deployment patterns.
  • Ideal for AI engineers, ML practitioners, and technical leaders.

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