Applied Claude AI Engineering: Designing Intelligent Agents and Scalable Pipelines Using LangChain, LangGraph, Model Context Protocol

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Bol This book provides a detailed examination of engineering practices for building advanced AI systems centered on Anthropic's Claude models. It focuses on the integration of LangChain for modular LLM application development, LangGraph for stateful agent orchestration and workflow management, and the Model Context Protocol (MCP) for standardized, secure connections to external data sources, tools, and services. Readers will explore architectural patterns for creating reliable, context-aware intelligent agents capable of complex reasoning and multi-step interactions. The content covers practical implementation strategies for constructing scalable pipelines that leverage MCP servers, adapt tools across distributed environments, and maintain consistency in long-running agent executions. Designed for experienced developers, AI engineers, and technical architects already familiar with Python-based LLM frameworks and agent concepts, this volume emphasizes production-grade design decisions, interoperability considerations, and performance optimization in real-world deployments. If you are ready to advance your capabilities in constructing sophisticated Claude-powered systems, add this resource to your library today.

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This book provides a detailed examination of engineering practices for building advanced AI systems centered on Anthropic's Claude models. It focuses on the integration of LangChain for modular LLM application development, LangGraph for stateful agent orchestration and workflow management, and the Model Context Protocol (MCP) for standardized, secure connections to external data sources, tools, and services. Readers will explore architectural patterns for creating reliable, context-aware intelligent agents capable of complex reasoning and multi-step interactions. The content covers practical implementation strategies for constructing scalable pipelines that leverage MCP servers, adapt tools across distributed environments, and maintain consistency in long-running agent executions. Designed for experienced developers, AI engineers, and technical architects already familiar with Python-based LLM frameworks and agent concepts, this volume emphasizes production-grade design decisions, interoperability considerations, and performance optimization in real-world deployments. If you are ready to advance your capabilities in constructing sophisticated Claude-powered systems, add this resource to your library today.

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Pagina's: 141, Paperback, Independently published


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Merk Independently Published
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  • 9798250265416
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