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MCP Server Development
A Hands-On Guide to Building Context-Aware AI Systems with OpenAI, Claude & LangChain
Angleščina
30 b
30 dni za vračilo blaga
Context is the new currency-and Model Context Protocol (MCP) is the protocol powering the next generation of enterprise‑grade AI. Whether you're a developer, engineer, or team lead, this book shows you how to build scalable, secure MCP servers that integrate OpenAI, Claude, and LangChain using real-world examples.
What You'll Gain
Architect Context‑Aware Servers: Learn step-by-step how to implement JSON‑RPC based MCP servers, handle snapshots and deltas, and add persistent memory with vector databases.
Hands‑On Projects: Dive into three production-scale projects-from chatbots to knowledge-base servers to automated workflows using Claude and LangChain.
Security & Compliance Built In: Equipped with GDPR-compliant erasure endpoints, structured logging, reviewer filters, and proactive red‑team simulations.
Enterprise CI/CD Toolkit: Automate rate-limit testing, predictive monitoring, dashboards, S3 publishing, Slack/Teams notifications, and auto‑remediation pipelines-all explained in code.
Diagnostics & Resilience: Includes appendices with detailed error matrices, structured logging schemas, troubleshooting exercises, a memory harness, and CI/CD dashboards.
Who This Book Is For
Developers building LLM-backed systems that require context awareness and memory.
Engineers & DevOps professionals responsible for secure, compliant, scalable deployments.
AI architects exploring multi-agent MCP workflows and LangChain integrations.
Book Structure at a Glance
SectionContentsFoundationsIntro to MCP, JSON‑RPC, architecture, memory snapshot/delta design
Core ImplementationBuild, test, persist, scale the basic server in Python, Node, or Go
Advanced FeaturesIntegration with OpenAI & Claude, LangChain and vector stores (FAISS, Pinecone)
Security & ComplianceAuth, encryption, GDPR/CCPA, red‑team walkthroughs, context isolation
Deployment & AutomationDocker/Kubernetes setups; GitHub Actions pipelines with dashboards and remediation
Why This Book Stands Out
Not just theory-working code: All examples are runnable and well-commented. You can clone the companion GitHub repo and deploy production-ready systems.
Enterprise-ready: Built with best practices in security, observability, testing, and self-healing.
Forward-looking: Covers predictive analytics, anomaly detection, multi-agent workflows, and scalable context pipelines.
Structured and engaging: Uses scenario-based explanations, troubleshooting case studies, and even quizzes and checklists for reinforcement.
With MCP Server Development, you're not just learning how to build-you're learning how to architect. Whether you're creating a chatbot that remembers weeks of interaction or an orchestration system that spans agents and vector databases, this book gives you the blueprint.
Join the growing ranks of engineers building the infrastructure for truly context-aware AI. Scroll up and grab your copy now - build smarter, safer, and more scalable context-aware systems today.
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