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
物品 #: 230168594

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

物品 #: 230168594

HKD 501

Price Details

Excluding Shipping & Custom charges ( Shipping and custom charges will be calculated on checkout )

*All items will import from EU

0 ratings 轉寫評價
有存貨
eu 從EU商店導入

QTY:

現在訂購,約可在下列時間收貨: 星期二, 十月 20
Our Top Logistics Partners
  • fedex
  • dhl
Engineer your own Python-based agentic AI framework with tool use memory and multi-agent workflows.
顯示更多
fast shipping

Fast
Shipping

free return

Free
Return*

secure packaging

Secure Packaging

100% original products

100% Original Products

pci-dss

PCI DSS Compliance

iso certified

ISO 27001 Certified


paypal payment
visa payment
mastercard payment

產品詳情

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 香港. 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
Dimensions 19.05 x 3.07 x 23.5 cm

產品敘述

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

有疑問? 與我們聊天

客戶問題與解答

  • 題: 如何從 Ubuy 在線購物 Design Multi-Agent AI Systems Using MCP and A2A:?

    回答: 從 Ubuy 在線購物 Design Multi-Agent AI Systems Using MCP and A2A: 非常簡單。. 您只需搜索產品,在結賬時選擇運輸方式,然後將其運送到您所在的位置。
  • 題: Design Multi-Agent AI Systems Using MCP and A2A: 可以在 Hong Kong 在線購物嗎?

    回答: 是的,您可以在 Ubuy Hong Kong 以合理的價格購買該產品。. Design Multi-Agent AI Systems Using MCP and A2A: 在本地不可用,但您可以信任我們的快遞服務。
  • 題: 下訂單後需要多長時間才能收到產品?

    回答: 您訂購的產品的交貨時間根據您訂購的商品和您選擇的運輸方式而有所不同。. 結賬時會提到預計送貨時間,所以購物時請放心。

English edition Gigi Sayfan Format: Paperback Editorial Review

未找到編輯評論

Customer Reviews & Ratings

4.3
9 客戶評分
  • 5 星
    53%
  • 4 星
    24%
  • 3 星
    23%
  • 2 星
    0%
  • 1 星
    0%

評價此產品

與其他客戶分享您的想法

Product Price History

重要資訊

  • 限制:如跨國購買產品,請注意製造商的保固有可能無效;製造商服務選項可能無法使用;產品手冊、教學、以及安全警示可能不會是目的地國家的語言;產品(與附加材料)設計也許不會符合目的地國家的標準、規格、以及標示要求;且產品也許不會符合目的地國家的伏特數值與其他電力標準(需要使用合適的變壓器或轉接器)。收件者須負責確定該產品在目的地國家可合法進口。當在 Ubuy 或其聯盟夥伴網站上訂購時,收件者為記錄上的進口者,且必須遵從目的地國家的法律與規範。
  • 由於 Ubuy 是一個全球搜尋引擎,並不是所有列於 Ubuy 的產品都有出售。產品須受出口/貿易法規規範。