Mcp Ai Agents
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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
MCP AI Agents
Author: MAXWELL. BROOKS
language: en
Publisher: Independently Published
Release Date: 2025-04-15
Build Smarter AI Agents That Use Real-World Context - Files, APIs, Databases, and More Are you tired of building chatbots that hallucinate, can't access external tools, or don't scale in real workflows? MCP AI Agents is the hands-on, code-first guide you've been looking for. Whether you're a Claude developer, OpenAI user, or AI engineer building with LangGraph, LangChain, or CrewAI, this book shows you how to turn LLMs into fully capable, context-aware agents that interact with real-world data using the Model Context Protocol (MCP). What You'll Learn - What is MCP and why it matters for tool-using AI - How to build JSON-RPC-compatible tool servers - Step-by-step guides to integrate Claude, GPT-4, and local APIs - Building agents that read PDFs, summarize text, query SQL, scrape the web, and generate reports - Exporting results, generating PDFs, and emailing stakeholders - Secure deployment using Docker, Railway, and Render - Future-proofing with LangGraph and multi-agent orchestration (CrewAI) Who This Book Is For AI developers working with Claude, OpenAI GPT-4, LangGraph, or Hugging Face Devs building retrieval-augmented generation (RAG) systems Teams looking to integrate LLMs into enterprise workflows Engineers exploring tool use, agent routing, and multi-step workflows Includes Real-World Projects Business Report Generator using Claude + file tools Web Research Agent with scraping, summarization, and citations Personal Productivity Assistant that plans your day and sends reminders API-integrated agents that pull weather, finance, or news data Knowledge assistant powered by vector search (FAISS, Chroma) Why MCP? The Model Context Protocol (MCP) is the new gold standard for secure, interoperable, and tool-aware AI workflows. It powers next-generation agents that can reason, act, and adapt using real-time context. Built for Production - Environment configuration with .env - API key security and access control - Logging, monitoring, and rate-limiting - Versioned tools and JSON manifest templates - Companion GitHub repository with full source code If you're serious about building agents that do more than chat, this book is your blueprint. No fluff. All code. Real-world power. Get your copy now and start building MCP agents that think, act, and deliver.
AI Agents and MCP Integration
Author: Andrew Albert
language: en
Publisher: Independently Published
Release Date: 2025-06-03
AI Agents and MCP Integration Developing Intelligent Agents Using Python, Gemini Flash, and MCP Servers Step into the future of automation with AI agents that think, act, and learn-all powered by the simplicity of Python and the power of MCP servers. Whether you're a software developer, data engineer, tech enthusiast, or AI hobbyist, this book will take you from zero to building intelligent, observable AI agents connected to modular control systems in under an hour. In this groundbreaking practical guide, you'll learn how to build, deploy, and scale your very own AI agents using Google's Gemini Flash via Google ADK, integrate them with an MCP (Modular Control Protocol) Server, extend them with custom tools, and observe every step of their reasoning using CometML's Opik. No more mystery boxes see your AI agent's thinking in action, step by step. By the end of this book, you won't just understand the theory you'll have a fully functional, intelligent agent running and connected to a server, ready to automate complex workflows and decisions in real time. What's Inside: Clear explanations of AI agents, their architecture, and how they interact with real-world systems A complete walkthrough of setting up your Python environment with Google ADK and Gemini Flash Building your first intelligent agent, piece by piece, even if you're new to agents or LLMs Creating custom tools for enhanced agent abilities Full integration with an MCP server, showing real-time connectivity and communication Visualizing agent decisions using Opik, a powerful observability framework from CometML Guidance on multi-step reasoning, debugging, and performance tuning Tips for deployment, scaling, and pushing your agent to production-ready stages A final hands-on project that ties everything together with clean, production-grade code Why This Book? Other AI books stop at chatbots or plug-and-play LLM APIs. This one goes deeper. You'll learn to build AI agents that are modular, dynamic, explainable, and connected to real systems. Whether you're exploring LLMs for the first time or you're an engineer ready to take your automations to the next level, this book is your gateway to hands-on AI deployment with real impact. Technologies Covered: Python 3.x Google ADK & Gemini Flash CometML's Opik (Agent Observability) MCP Server Architecture Tooling, API Integration, and Custom Logic Design Get ready to code. Get ready to connect. Get ready to think like an agent.