AI Agents and MCP Integration: Developing Intelligent Agents Using Python, Gemini Flash, and MCP Servers
商品資訊
ISBN13:9798286743506
出版社:Independently published
作者:Andrew Albert
出版日:2025/06/03
裝訂:平裝
規格:25.4cm*17.8cm*0.9cm (高/寬/厚)
重量:313克
商品簡介
商品簡介
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:
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:
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
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
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