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Model Context Protocol for LLMs. Build scalable multi-agent AI systems with LangChain, AutoGen, and the MCP open standard Naveen Krishnan

(ebook) (audiobook) (audiobook) Język publikacji: angielski
Model Context Protocol for LLMs. Build scalable multi-agent AI systems with LangChain, AutoGen, and the MCP open standard Naveen Krishnan - okladka książki

Model Context Protocol for LLMs. Build scalable multi-agent AI systems with LangChain, AutoGen, and the MCP open standard Naveen Krishnan - okladka książki

Model Context Protocol for LLMs. Build scalable multi-agent AI systems with LangChain, AutoGen, and the MCP open standard Naveen Krishnan - audiobook MP3

Model Context Protocol for LLMs. Build scalable multi-agent AI systems with LangChain, AutoGen, and the MCP open standard Naveen Krishnan - audiobook CD

Autor:
Naveen Krishnan
Ocena:
AI developers face a growing challenge: building intelligent systems that retain long-term memory, reason over dynamic context, and integrate safely with external tools. Model Context Protocol for LLMs provides a modern solution—offering an open, modular architecture to construct scalable LLM agents with structured context exchange.
This book equips you with a complete hands-on journey to MCP. You’ll implement the protocol’s key components—resource providers, tool providers, and gateways—then use these to orchestrate agents, chain workflows, and add context-aware behavior. You’ll also learn how MCP integrates seamlessly with LangChain, AutoGen, RAG systems, and multimodal applications.
Security and governance are covered in depth, helping you build privacy-compliant, threat-resistant AI apps. You’ll explore caching, async tasks, load balancing, and scaling strategies for real-world readiness. With a continuous hands-on project, MCP becomes more than a standard—it becomes a blueprint for production-grade LLM development.

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O autorze książki

Professional Profile
AI & Cloud Solutions Architect with 16+ years of success leading enterprise-grade digital transformation initiatives across Retail, Banking, Healthcare, and Manufacturing sectors. Well known for building scalable AI systems, integrating LLMs in production, and architecting secure, cloud-native applications. A Fellow of BCS and Senior IEEE Member, AI lead at Microsoft, open-source contributor, and frequent speaker at global technology forums and Podcasts.
Key Achievements:
Designed and deployed advanced Retrieval-Augmented Generation (RAG) and Voice RAG systems for Fortune 500 enterprises.
Architected large-scale, context-aware agent systems using AutoGen, LangChain, and Model Context Protocol (MCP).
Judge at Global NASA Space Apps, Microsoft Global Hackathon evaluating cutting-edge AI projects.
Authored over 35 technical blogs, academic papers.
Spoke on 20+ podcast in US, Australia, Europe, UK
Core Technical Competencies:
Enterprise AI & Multi-Agent System Architecture
Microsoft Azure, GCP, AWS – Cloud-Native Design
LLM Integration, RAG, LangChain, AutoGen
MLOps, DevOps, CI/CD for AI Pipelines
Distributed Systems, Microservices, Event-Driven Design
AI Ethics, Governance, and Responsible AI
Thought Leadership, Mentorship, and Public Speaking

Packt Publishing - inne książki

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