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Learn Model Context Protocol with Python

You're reading from   Learn Model Context Protocol with Python Build agentic systems in Python with the new standard for AI capabilities

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Product type Paperback
Published in Oct 2025
Publisher Packt
ISBN-13 9781806103232
Length 304 pages
Edition 1st Edition
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Author (1):
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Christoffer Noring Christoffer Noring
Author Profile Icon Christoffer Noring
Christoffer Noring
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Toc

Table of Contents (17) Chapters Close

Preface 1. Introduction to the Model Context Protocol 2. Explaining the Model Context Protocol FREE CHAPTER 3. Building and Testing Servers 4. Building SSE Servers 5. Streamable HTTP 6. Advanced Servers 7. Building Clients 8. Consuming Servers 9. Sampling 10. Elicitation 11. Securing Your Application 12. Bringing MCP Apps to Production 13. Unlock Your Book’s Exclusive Benefits 14. Other Books You May Enjoy
15. Index
Appendix: Building for the Web with Modern Python

Working with an LLM

There are many AI providers out there that let you call an LLM. In this book, we will use GitHub Models, as that’s a free option, and all you need to use it is a GitHub account. To use GitHub Models, you will either need to start your project in GitHub Codespaces or set up a personal access token (PAT) with the right permissions. The reason you need a token in the first place is that you are calling an API, and the token is used as a bearer token to authenticate the request. To use a local AI model via, for example, Ollama, you wouldn’t need a token. You can type the token directly in the source code, but it’s recommended to keep it in an environment variable for security reasons.

So, what do we need to know if we’ve never worked with AI before? Well, the idea is to send in a prompt and get back a response. The prompt is natural language text that describes what you want the LLM to do. The response is also natural language text that...

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