Model Context Protocol Mcp In Ai Agents 2nd Edition
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Model Context Protocol (MCP) in AI Agents, 2nd Edition
Author: Morgan Devline
language: en
Publisher: Independently Published
Release Date: 2025-05-27
Model Context Protocol (MCP) in AI Agents, 2nd Edition The Ultimate Guide to Building Context-Aware, Integrated, and Intelligent AI Systems If you're building with large language models (LLMs), multi-agent AI systems, or next-gen automation tools like OpenAI Assistants, AutoGen, LangChain, Claude, or CrewAI-this book is your blueprint for context-aware AI development. In this fully updated 2nd Edition, you'll master the Model Context Protocol (MCP)-a breakthrough open standard that bridges LLMs with live, structured external data using clean JSON-RPC calls. Whether you're a developer, ML engineer, system architect, or product builder, this guide shows you how to scale AI agents beyond simple prompts into reliable, interoperable, and real-world-ready tools. What's New in the Second Edition? ✅ Deep coverage of MCP v2.1 (structured context_spec, context_value, validation logic) ✅ New full-stack projects: news summarizer, doc retriever, financial dashboard agents ✅ Native integration patterns with Claude, GPT-4-turbo tools, and OpenAI Assistants v2 ✅ Multi-agent context routing and shared context architectures ✅ Advanced scaling strategies: Docker, Redis, n8n, OpenTelemetry, and load balancing ✅ Security, privacy, and compliant context sharing built-in Inside You'll Learn How To: ✔ Build your own MCP-compliant context servers with FastAPI ✔ Connect agents to live APIs, file systems, databases, and embeddings ✔ Implement stateless, testable context handlers for any agent runtime ✔ Cache, scale, and monitor context pipelines in production ✔ Use MCP in LangGraph, CrewAI, and AutoGen workflows ✔ Future-proof your LLM stack with interoperable agent design Built for real-world engineers, this book includes runnable code, test payloads, curl-ready examples, no-fluff architectural guidance, and GitHub companion resources. Whether you're integrating with GPT, Claude, or rolling your own multi-agent crew, Model Context Protocol (MCP) in AI Agents gives you the tools, patterns, and precision you need to build the next generation of modular, intelligent, context-aware AI systems.
MCP AI Agents, 2nd Edition
Author: Dr Maxwell Brooks
language: en
Publisher: Independently Published
Release Date: 2025-05-28
Are you tired of building chatbots that hallucinate, can't connect to external tools, or don't scale in real workflows? MCP AI Agents, 2nd Edition is the hands-on, code-first guide you've been looking for. Now fully updated for 2025, it teaches AI developers how to build Claude AI agents and OpenAI-driven assistants that truly understand context and act on real-world data. You'll learn to harness the open Model Context Protocol (MCP) - a JSON-RPC 2.0 integration layer - to give your agents tools, memory, and connectivity beyond basic chat. This second edition delivers production-grade AI infrastructure, step-by-step projects, and cutting-edge techniques to create robust context-aware AI systems from scratch. What You'll Learn MCP Fundamentals & JSON-RPC 2.0: Master the Model Context Protocol (MCP) and why it's a game-changer for tool-enhanced AI (over 1,000 community-built MCP connectors for Slack, GitHub, databases, etc. exist as of 2025). Learn how to build MCP JSON-RPC servers and securely expose files, APIs, databases, and more to your agents. Claude API Integration & OpenAI Tools: Step-by-step guidance to integrate Claude's API and OpenAI's latest function-calling capabilities into your agents. Work through examples of Claude API integration and GPT-4 tool use, so your AI can search documents, call web services, and execute code seamlessly. Agent Frameworks with Claude/OpenAI: Explore leading agent orchestration frameworks and techniques. You'll connect agent frameworks with Claude/OpenAI models using LangChain and open-source adapters, and compare approaches like OpenAI's functions vs Anthropic's Claude for building flexible agents. Multi-Step Workflows and Tools: Design tool-enhanced workflows that chain LLM reasoning with multi-step tool usage. Build agents that read PDFs, query SQL databases, scrape the web, and summarize content with citations - then output results to reports or emails. Each project is broken down into clear, step-by-step tasks for easy follow-along. LangGraph and CrewAI Orchestration: Orchestrate complex tasks with multi-agent systems. Learn to coordinate LangGraph agents (DAG-based flows) and CrewAI role-based teams, leveraging MCP to share context and tools. The book demonstrates how frameworks like LangGraph and CrewAI can be supercharged with MCP for scalable, collaborative agents. Deployment & Infrastructure: Get practical advice on deploying production-grade AI infrastructure. Containerize your agents with Docker and integrate into CI/CD pipelines. Deploy on cloud platforms (Railway, Render, AWS) with authentication and monitoring, ensuring your AI agents are secure and ready for real-world agent deployments. New in the 2nd Edition Latest APIs & Models: Updated examples featuring Claude's newest capabilities and OpenAI's evolving API (GPT-4/GPT-3.5 Turbo updates, function calling, etc.), so you're working with state-of-the-art tools. n8n Workflow Integration: A brand-new chapter on using n8n (no-code automation) as an MCP host - learn to plug your AI agents into enterprise workflows and automation pipelines with ease. Expanded Multi-Agent Coverage: In-depth guidance on building distributed agent systems, with new content on LangGraph orchestration and CrewAI enhancements. Discover how the 2nd edition future-proofs your skills for the era of collaborative, context-sharing AI agents. More Real-World Projects: Additional hands-on projects and case studies, including new examples of agents in business intelligence, DevOps assistance, and personal productivity - all with complete, tool-enhanced workflowsand code provided
🤝 The Model Context Protocol: Unifying AI Communication
🤝 The Model Context Protocol: Unifying AI Communication This episode introduces the Model Context Protocol (MCP), an open standard designed to enable seamless communication between AI agents and external data sources or tools, much like a universal adaptor. It addresses the "N×M" integration problem where connecting numerous AI models to various tools creates an unsustainable development burden. The show explains MCP's three-tier architecture consisting of a Host (the user-facing application), an MCP Client (which manages sessions), and an MCP Server (which translates requests for data sources like databases or APIs). Furthermore, it details how MCP uses JSON-RPC 2.0 for messaging and supports dynamic discovery of capabilities, alongside critical security principles for implementation. Finally, it distinguishes MCP from other standards, highlighting its complementary role with the Agent-to-Agent (A2A) Protocol for multi-agent collaboration. Audio at 🛠️ AI Unraveled Builder's Toolkit - Build & Deploy AI Projects—Without the Guesswork: E-Book + Video Tutorials + Code Templates for Aspiring AI Engineers Start building today: Get Full access to the AI Unraveled Builder's Toolkit (Videos + Audios + PDFs) at https://djamgatech.myshopify.com/products/%F0%9F%9B%A0%EF%B8%8F-ai-unraveled-the-builders-toolkit-practical-ai-tutorials-projects-e-book-audio-video