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
Stavka #: 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

Stavka #: 242970796

€ 68

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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.

Detalji o proizvodu

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 Croatia. 1806116472
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.

OPIS PROIZVODA

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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Pitanja i odgovori kupaca

  • pitanje: Kako kupovati Design Multi-Agent AI Systems Using MCP and A2A: online od Ubuya?

    odgovor: Jednostavno je kupovati Design Multi-Agent AI Systems Using MCP and A2A: online s Ubuya.. Samo trebate potražiti proizvod, odabrati način dostave tijekom odjave i dobiti ga na svoju lokaciju.
  • pitanje: Je li Design Multi-Agent AI Systems Using MCP and A2A: dostupan za online kupnju u Croatia?

    odgovor: Da, na Ubuyu Croatia ovaj proizvod vam je dostupan za kupnju po razumnoj cijeni.. Design Multi-Agent AI Systems Using MCP and A2A: nije dostupan lokalno, ali možete nam povjeriti naše usluge ekspresne dostave.
  • pitanje: Koliko dugo je potrebno da dobijete proizvod nakon narudžbe?

    odgovor: Vrijeme isporuke vašeg naručenog proizvoda ovisi o tome što ste naručili i načinu dostave koji ste odabrali.. Predviđeno vrijeme dostave navedeno je tijekom procesa naplate, stoga budite bezbrižni prilikom kupovine.

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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Pros

  • 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

Protiv

  • Publication date is in the future, 2026

Product Price History

Važne informacije

  • Ograničenja: imajte na umu da jamstvo možda ne vrijedi za proizvode koji se dostavljaju u inozemstvo; servis možda neće biti dostupan; priručnici proizvoda, upute i sigurnosna upozorenja možda nisu na jeziku zemlje odredišta; proizvodi (i prateći materijali) možda nisu u skladu sa standardima, specifikacijama i zahtjevima za označavanje zemlje odredišta; proizvod možda nije usklađen s naponom struje i drugim električnim standardima (zbog čega će možda trebati adapter ili pretvarač). Primatelj je odgovoran za provjeru može li proizvod prema važećim zakonima biti uvezen u zemlju odredišta. Kad naručujete od Ubuya ili njegovih partnera, primatelj se smatra registriranim uvoznikom i mora se pridržavati svih zakona i propisa zemlje odredišta.
  • Svi proizvodi navedeni na Ubuyu nisu za prodaju, jer je Ubuy globalna tražilica. Proizvodi podliježu propisima o izvozu i trgovini.