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Learn Model Context Protocol with Python

Learn Model Context Protocol with Python

By : Christoffer Noring
4.5 (2)
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Learn Model Context Protocol with Python

Learn Model Context Protocol with Python

4.5 (2)
By: Christoffer Noring

Overview of this book

Learn Model Context Protocol with Python introduces developers, architects, and AI practitioners to the transformative capabilities of Model Context Protocol (MCP), an emerging protocol designed to standardize, distribute, and scale AI-driven applications. Through the lens of a practical project, the book tackles the modern challenges of resource management, client-server interaction, and deployment at scale. Drawing from Christoffer's expertise as a published author and tutor at the University of Oxford, you’ll explore the components of MCP and how they streamline server and client development. Next, you’ll progress from building robust backends and integrating LLMs into intelligent clients to interacting with servers via tools such as Claude for desktop and Visual Studio Code agents. The chapters help you understand how to describe the capabilities of hosts, clients, and servers, facilitating better interoperability, easier integration, and clearer communication between different components. The book also covers security best practices and building for the cloud, ensuring that you're ready to deploy your MCP-based apps. Each chapter enables you to develop hands-on skills for building and operating MCP-based agentic apps. The Python primer at the end rounds out the practical toolkit, making this book essential for any team building AI-native applications today.
Table of Contents (17 chapters)
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14
Other Books You May Enjoy
15
Index

uv: your development environment manager

Let’s cover our last topic in this appendix, namely, uv. It’s not something you must use, but you’re highly recommended to do so. Here’s why:

  • It provides a consistent interface for managing your development environment. It means you can easily switch between different projects and their dependencies without worrying about conflicts.
  • It streamlines the process of setting up and managing virtual environments, making it easier to work on multiple projects with different requirements. So, instead of typing python -m venv env and source env/bin/activate, you can simply use uv init to create and activate a virtual environment, which also initiates your project.
  • It simplifies the process of installing and managing dependencies, allowing you to easily add, remove, and update packages as needed. You’re used to typing pip install <package> to install a package, but with uv, you can use uv...
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Learn Model Context Protocol with Python
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