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Model Context Protocol for LLMs. Build scalable multi-agent AI systems with LangChain, AutoGen, and the MCP open standard
Naveen Krishnan
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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.
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.
- 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
- Назва:Model Context Protocol for LLMs. Build scalable multi-agent AI systems with LangChain, AutoGen, and the MCP open standard
- Автор:Naveen Krishnan
- Оригінальна назва:Model Context Protocol for LLMs. Build scalable multi-agent AI systems with LangChain, AutoGen, and the MCP open standard
- ISBN:9781806662265, 9781806662265
- Дата видання:2026-02-27
- Формат:Eлектронна книга
- Ідентифікатор видання: e_4mzr
- Видавець: Packt Publishing
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