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Learn Model Context Protocol with Python

Learn Model Context Protocol with Python

By : Christoffer Noring
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Learn Model Context Protocol with Python

Learn Model Context Protocol with Python

4 (1)
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

Operations and observability

Once your application is in production, there’s a set of problems we need to address:

  • Observability: Do you know how your app is doing? Is it under load, is it slow, is it failing, and is it secure?
  • Scalability and resilience: Can your app handle traffic spikes? Can it scale up and down, and is it resilient to failures?
  • Monitoring and feedback: Do you know when something goes wrong? Can you alert the right people, and do you have a feedback loop to improve the app over time?
  • Governance and compliance: Are you compliant with regulations? Do you have the right policies in place, and are you managing data responsibly?
  • Future proofing: Are you prepared for future changes? Can you adapt to new technologies, and are you continuously improving your app?

Observability

Do you know how your app is doing, really? If you do, that means you’ve been diligent in terms of adding logging, tracing, and metrics...

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Learn Model Context Protocol with Python
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