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Model Context Protocol (MCP) in Agentic RAG Systems: Building, Scaling, and Securing Agentic AI with MCP: Dynamic RAG, Tool Discovery, Interoperability, and Observability
Transform how your AI agents think, act, and adapt—streamlining complex workflows with a single, standards-based protocol.
Book Summary
Model Context Protocol (MCP) is the missing link between powerful language models and real-world systems, empowering AI agents to call dynamic tools, fetch fresh data, and maintain state—safely and at scale. This book guides you from the fundamentals of Retrieval-Augmented Generation (RAG) to advanced multi-agent orchestration, showing you precisely how to integrate, secure, and monitor MCP-driven pipelines in production environments.
You’ll discover how to replace brittle, ad-hoc prompt hacks with a robust JSON-RPC manifest that self-documents every resource and tool your agents can use. Learn best practices for hybrid retrieval, efficient context streaming, transactional tool bundles, and cross-platform bridges—complete with copy-and-paste code examples in Python, TypeScript, Go, and more. Each chapter is packed with real-world case studies from manufacturing, FinTech, and healthcare, illustrating how MCP slashed downtime, cut support costs by 86 %, and accelerated critical chart pulls from 90 to 8 seconds.
Whether you’re an ML engineer, SRE, security lead, or product manager, this hands-on playbook equips you with the strategies, patterns, and extensions to confidently deploy agentic RAG systems. You’ll learn how to enforce scopes with OAuth 2.1/JWT, encrypt and redact sensitive data, implement observability with Prometheus and OpenTelemetry, and contribute to the evolving open-source MCP community—ensuring your solutions stay ahead of emerging standards.
What’s Inside
End-to-End MCP Quick-Start: Spin up manifest-driven servers and clients in minutes, then register your first tools and resources.
Advanced Retrieval & Tool Calling: Master hybrid index strategies, streaming diff resources, and schema-driven tool invocation to minimize latency and token spend.
Security & Compliance Playbook: Implement OAuth 2.1, mTLS, data redaction, and immutable audit logs to satisfy GDPR, HIPAA, and PCI-DSS requirements.
Observability & Debugging: Instrument every call with metrics, traces, and structured logs—plus runbooks and replay tools for lightning-fast root-cause analysis.
Extensibility & Governance: Draft your own extensions, bridge to OpenAI Functions and Google A2A, and participate in the MCP spec governance model.
Elevate your AI from proof-of-concept to mission-critical reliability—grab your copy of Model Context Protocol in Agentic RAG Systems today and build the next generation of smart, scalable, and secure AI agents.
Book Summary
Model Context Protocol (MCP) is the missing link between powerful language models and real-world systems, empowering AI agents to call dynamic tools, fetch fresh data, and maintain state—safely and at scale. This book guides you from the fundamentals of Retrieval-Augmented Generation (RAG) to advanced multi-agent orchestration, showing you precisely how to integrate, secure, and monitor MCP-driven pipelines in production environments.
You’ll discover how to replace brittle, ad-hoc prompt hacks with a robust JSON-RPC manifest that self-documents every resource and tool your agents can use. Learn best practices for hybrid retrieval, efficient context streaming, transactional tool bundles, and cross-platform bridges—complete with copy-and-paste code examples in Python, TypeScript, Go, and more. Each chapter is packed with real-world case studies from manufacturing, FinTech, and healthcare, illustrating how MCP slashed downtime, cut support costs by 86 %, and accelerated critical chart pulls from 90 to 8 seconds.
Whether you’re an ML engineer, SRE, security lead, or product manager, this hands-on playbook equips you with the strategies, patterns, and extensions to confidently deploy agentic RAG systems. You’ll learn how to enforce scopes with OAuth 2.1/JWT, encrypt and redact sensitive data, implement observability with Prometheus and OpenTelemetry, and contribute to the evolving open-source MCP community—ensuring your solutions stay ahead of emerging standards.
What’s Inside
End-to-End MCP Quick-Start: Spin up manifest-driven servers and clients in minutes, then register your first tools and resources.
Advanced Retrieval & Tool Calling: Master hybrid index strategies, streaming diff resources, and schema-driven tool invocation to minimize latency and token spend.
Security & Compliance Playbook: Implement OAuth 2.1, mTLS, data redaction, and immutable audit logs to satisfy GDPR, HIPAA, and PCI-DSS requirements.
Observability & Debugging: Instrument every call with metrics, traces, and structured logs—plus runbooks and replay tools for lightning-fast root-cause analysis.
Extensibility & Governance: Draft your own extensions, bridge to OpenAI Functions and Google A2A, and participate in the MCP spec governance model.
Elevate your AI from proof-of-concept to mission-critical reliability—grab your copy of Model Context Protocol in Agentic RAG Systems today and build the next generation of smart, scalable, and secure AI agents.
304 pages, Kindle Edition
Published July 4, 2025
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