Mcp With Ai
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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
Mastering Model Context Protocol (MCP) for AI Developers
Author: Camila Jones
language: en
Publisher: Independently Published
Release Date: 2025-06-07
Mastering Model Context Protocol (MCP) for AI Developers: Shared Memory, Multi-Agent Coordination, and Next-Gen AI Systems Unlock the next evolution of AI system design with the definitive hands-on guide to the Model Context Protocol (MCP)-the emerging backbone for multi-agent, context-aware, and scalable AI workflows. This book is your comprehensive companion to architecting, deploying, and maintaining advanced AI agents and automation using MCP, whether you're building enterprise solutions, research prototypes, or cloud-native platforms. Inside, you'll discover: The Core of MCP: Grasp the principles behind MCP-session context, shared memory, agent orchestration, and protocol standards-through detailed explanations and well-structured walkthroughs. Real-World Implementation: Set up a modern MCP development environment from scratch, connect with Python, Node.js, and more, and rapidly build production-grade agents and orchestrators. Context-Aware Workflows: Learn to design and operate agents that dynamically read, write, and share memory, powering everything from chatbots to complex multi-agent business automation. Multi-Agent Coordination and Orchestration: Dive deep into robust architectures, agent discovery, distributed context synchronization, event streaming, and scalable deployment strategies for high-availability systems. Advanced Features and Extensions: Extend MCP for RAG (Retrieval-Augmented Generation), LLM orchestration, real-time updates, authentication, and secure, compliant AI workflows. Field-Tested Best Practices: Benefit from comprehensive troubleshooting guides, versioning strategies, and in-depth case studies-including conversational AI platforms, RAG pipelines, and industry deployments in robotics, cloud AI, and enterprise automation. Future-Proof Your Solutions: Explore the evolving MCP ecosystem, standards integration, roadmap for extensions, and practical guidance for connecting with OpenAI, Claude, Hugging Face, and emerging agent marketplaces. Why This Book? Perfect for AI developers, machine learning engineers, system architects, and automation professionals, this book is meticulously structured to take you from foundational concepts to advanced, real-world solutions. No unnecessary filler-just actionable theory, clean code samples, configuration playbooks, troubleshooting cheatsheets, and up-to-date workflows. Stay Ahead in Agentic AI: With the world moving to multi-agent, context-driven AI, MCP is fast becoming the industry standard for building transparent, scalable, and resilient intelligent systems. This guide ensures you stay at the forefront of the next generation of AI-ready to deploy robust solutions in production today and evolve with tomorrow's innovations.
AI in the Movies
Author: Paula Murphy
language: en
Publisher: Edinburgh University Press
Release Date: 2024-04-30
AI in the Movies analyses film representations of artificial intelligence, from their first emergence in the 1950s up to 2020. These strong or general artificial intelligences take different forms: some are digital AIs, some robot AIs, some move between material and digital forms. Some are indistinguishable from humans, and some have no material existence at all. Analysis of these representations demonstrates filmmakers eroding the division between human and AI, by presenting character doubles, narrative parallels and eventually, identities in which the biological and artificial overlap and intersect in new hybrid forms.The book identifies the aspects of AI science that fascinate filmmakers and outlines the key themes and tropes in AI film, including parent-child relationships, the female robot, human-AI doubles, parallels and hybrids, and AI death and mortality.