Model Context Protocol for LLMs
Build secure, scalable, and context-aware AI agents using a standardized protocol
Created by Naveen Krishnan
Discover how to design secure, modular, and scalable AI agents by mastering the Model Context Protocol. Learn to connect popular frameworks like LangChain, AutoGen, and RAG, and build context-aware systems ready for real-world deployment. Gain practical skills for building reliable, production-grade LLM solutions.
Packt | Feb 2026 | 436 min
What You Will Learn
You will start by understanding the foundations of context management and multi-agent systems. Step by step, you will build MCP components, integrate them with leading frameworks, and apply these skills to enterprise scenarios. Practical examples and architecture patterns help you reinforce each concept as you progress.
Key Features
- Design modular AI agents with standardized context management for reliability
- Integrate LangChain, AutoGen, and RAG to enable collaborative multi-agent workflows
- Apply security and scaling strategies to confidently deploy AI systems in production
Target Audience
Ideal for AI and ML engineers, software developers, and solution architects working with LLM-powered applications. If you have intermediate Python skills, know LLM concepts and REST APIs, and want to build secure, scalable AI systems, you will find clear guidance and actionable techniques throughout.
