AI developers face a growing challenge: building intelligent systems that retain long-term memory, reason over dynamic context, and integrate safely with external tools. Model Context Protocol for LLMs provides a modern solution—offering an open, modular architecture to construct scalable LLM agents with structured context exchange.
This book equips you with a complete hands-on journey to MCP. You’ll implement the protocol’s key components—resource providers, tool providers, and gateways—then use these to orchestrate agents, chain workflows, and add context-aware behavior. You’ll also learn how MCP integrates seamlessly with LangChain, AutoGen, RAG systems, and multimodal applications.
Security and governance are covered in depth, helping you build privacy-compliant, threat-resistant AI apps. You’ll explore caching, async tasks, load balancing, and scaling strategies for real-world readiness. With a continuous hands-on project, MCP becomes more than a standard—it becomes a blueprint for production-grade LLM development.

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Spis treści

Model Context Protocol for LLMs. Build scalable multi-agent AI systems with LangChain, AutoGen, and the MCP open standard eBook -- spis treści

• 1. Introduction to Model Context Protocol
• 2. Building a Basic Agent with State and Deployment Flow
• 3. MCP for Non-Technical Readers Workflows
• 4. MCP Components and Interfaces
• 5. MCP Architecture Overview
• 6. Server-Side Implementation
• 7. Client-Side Integration
• 8. MCP Security Model
• 9. MCP Performance Optimization
• 10. MCP and Multi-Agent Systems
• 11. MCP for Retrieval-Augmented Generation
• 12. MCP and LangChain Integration
• 13. MCP and AutoGen Integration
• 14. MCP for Enterprise Knowledge Management
• 15. MCP for Personalization and Recommendation Systems
• 16. MCP for Multimodal Applications
• 17. Enterprise Knowledge Management
• 18. Case Studies and Applications
• 19. Ethical Considerations and Responsible AI with MCP
• 20. Advanced Topics and Future Directions