Model Context Protocol
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Model Context Protocol
Explore AI Agents and Model Context Protocol with practical guides to setting up MCP servers across popular tools like Gmail, Slack, and Excel. Learn how AI can revolutionize task automation. Key Features In-depth coverage of generative AI and large language models Step-by-step installation guides for MCP servers across various tools Practical applications of AI agents with real-world use cases Book DescriptionThis book offers a detailed introduction to the groundbreaking field of AI agents and Model Context Protocol (MCP). The first section delves into generative AI and large language models (LLMs), exploring how these technologies power modern AI systems. From there, the book introduces the concept of AI agents—autonomous systems capable of executing tasks with varying levels of complexity. Moving into practical applications, the book focuses on Model Context Protocol, explaining its key components and how it enables effective interaction between AI and various software tools. Each chapter offers step-by-step instructions for setting up MCP servers for popular tools like Gmail, YouTube, GitHub, and more, empowering readers to automate tasks and streamline workflows. The book concludes by addressing the future of MCP, its potential risks, and how to stay safe while using these advanced technologies. Whether you're a beginner or experienced practitioner, this guide will deepen your understanding of AI and enhance your ability to leverage cutting-edge automation in daily operations.What you will learn Understand the principles of generative AI and LLMs Learn about the core concepts of AI agents and their roles Explore the importance of the Model Context Protocol Set up MCP servers for tools like Gmail, Excel, and Slack Apply MCP with local LLMs using Ollama Install MCP servers for platforms like YouTube and GitHub Who this book is for This book is ideal for AI enthusiasts, developers, and tech professionals interested in learning about AI agents, task automation, and Model Context Protocol. The audience should have a basic understanding of AI concepts and be familiar with popular software tools like Gmail, Slack, and Excel. While no advanced programming skills are required, readers should be comfortable following installation steps and exploring real-world applications. This guide is perfect for anyone looking to integrate AI into their business processes or personal projects.
The Model Context Protocol Detailed Guide
Author: Kian Trevella
language: en
Publisher: Independently Published
Release Date: 2025-11-14
Artificial Intelligence has evolved beyond simple model queries - it now depends on context. Every AI response, decision, and recommendation is shaped by the information it can recall, interpret, and maintain. Yet, until recently, context handling was fragmented, inconsistent, and inefficient across systems. Enter the Model Context Protocol (MCP) - a transformative framework that standardizes how AI systems understand, share, and synchronize context across models and environments. MCP represents a major leap toward intelligent, multi-agent collaboration and persistent contextual reasoning - the backbone of modern agentic AI systems. This book serves as your complete roadmap to mastering MCP - from its fundamental concepts to hands-on implementation within advanced AI ecosystems like LangChain, LlamaIndex, and OpenAI's Assistant API. You'll discover how to integrate MCP into your workflows, optimize context windows, and engineer systems that think, remember, and evolve dynamically. By the end, you'll not only understand how MCP works, but also how to use it to power next-generation autonomous AI systems with unmatched precision and scalability.
Model Context Protocol (MCP) Servers in Python
Author: Newman Chandler
language: en
Publisher: Independently Published
Release Date: 2025-09-04
Model Context Protocol (MCP) Servers in Python: Build production-ready FastAPI & WebSocket MCP servers that power reliable LLM integrations Modern AI demands more than just smart models, it requires robust infrastructure that connects, manages, and scales Large Language Models (LLMs) with reliability and speed. As the backbone for secure, real-time, and context-aware LLM workflows, Model Context Protocol (MCP) servers have become an essential building block for developers and teams who are serious about production-grade AI. Are you struggling to build seamless LLM-powered applications, or looking for a proven architecture that delivers speed and reliability at scale? This book offers the practical blueprint you need. Model Context Protocol (MCP) Servers in Python is the hands-on guide for engineers and architects ready to move from fragmented prototypes to scalable, production-ready MCP server infrastructure. Harness the power of FastAPI and WebSocket to orchestrate context-driven AI workloads, route messages, manage memory, enforce security, and deliver high-throughput, low-latency integrations across diverse LLMs. Inside, you'll learn how to: Build MCP servers from scratch using FastAPI and Python, ready for cloud deployment. Implement bi-directional streaming with WebSocket to enable true real-time interactions. Architect context stores, session management, and robust memory for multi-turn conversations and agent workflows. Secure your server with authentication, RBAC, secrets management, and modern API security best practices. Integrate LLMs and agent tools for advanced automation and agentic pipelines. Optimize for scalability, observability, and fault tolerance in real production environments. Whether you're building internal developer platforms, custom RAG pipelines, or AI-powered chat, this book distills the patterns, code, and strategies required to achieve reliability and velocity in your MCP stack. Every chapter delivers practical insight, hands-on labs, and fully runnable code examples verified against the latest Python and FastAPI releases. If you're ready to transform your LLM applications from experiments to production systems, this is the definitive guide you've been searching for. Start building reliable, scalable, and secure MCP servers in Python, take your AI integrations to the next level now.