Building Intelligent AI Backends with MCP: A Developer’s Guide to Model Context Protocol Servers and Tool APIs
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Peso con empaque:
0.33 kg
0.33 kg
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Producto de:
Amazon
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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