Artículo: AMZ-B0F9X4MWKC

Building Intelligent AI Backends with MCP: A Developer’s Guide to Model Context Protocol Servers and Tool APIs

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Sin stock

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0.20 kg

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No

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Amazon

Sobre este producto

The fundamental principles of Model Context Protocols, including how they differ from REST and GraphQL.
How to architect scalable MCP servers, build context brokers, and integrate modular tool APIs.
Techniques to implement shared memory, embedding-based retrieval, and RAG (retrieval-augmented generation) for intelligent reasoning.
Strategies to build autonomous workflows using dynamic agent loops, task graphs, and orchestration with Temporal or Prefect.
Full-stack implementation guidance with modern tooling: FastAPI, Pydantic v3+, Poetry, Docker, Redis, SQLite, FAISS, and more.
Deep dives into security, observability, fault-tolerance, token budgeting, and production-grade deployment strategies.
How to govern AI backends with access controls, sandboxed toolchains, consent auditing, and lifecycle versioning.
It’s the first book to treat MCP architecture as a primary development target—not just an integration concept.
Unlike AI books that focus on models alone, this guide teaches you to build the intelligent infrastructure that makes large language models usable, dependable, and production-ready.
Richly practical yet conceptually deep, it blends hands-on engineering with systemic architectural insight, always grounded in modern, real-world tools.
Every section is carefully designed to help you think like a backend engineer for LLM-powered systems, not just copy examples.
It focuses on developer empowerment, enabling you to build modular, reusable, and intelligent AI systems that are maintainable and future-proof.
Backend developers and DevOps engineers looking to break into intelligent system design.
AI engineers and ML ops professionals seeking practical approaches to orchestration, tooling, and context memory.
Software architects designing LLM-integrated infrastructure at scale.
Product engineers working on tools, chatbots, assistants, or autonomous agents.
Any developer serious about understanding how to build reliable, scalable, and intelligent software backends powered by large models and modular APIs.

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