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MCP (Model Context Protocol) is quickly becoming the standard way to give AI assistants real-world capabilities by exposing focused, versioned tools that compatible clients such as Claude Code, Codex, and Cursor can call at runtime. In this tutorial, we will build a Stock News MCP Server in Python with FastMCP, containerize it with Docker, deploy it to Google Cloud Run, and connect it to Claude Code so you can fetch live market news with a stock ticker.

So you have built a Python package, it works great on your machine, and now you want to anyone to run pip install <package> to use it. That last mile - from "runs locally" to "installable from PyPI with one command" - turns out to be a headache to a surprising number of people because it's conceptually hard. This tutorial cuts through that friction. We will use a real project called lucky-cli - a lottery ticket generator/checker CLI package - to walk you through the practical steps after development: building the package, versioning it automatically, setting up PyPI credentials, and wiring a CI pipeline via GitHub Actions for making predictable, repeatable, and safe releases.

Running a blog doesn't have to mean maintaining a server 24/7 -- especially when the traffic is low or unpredictable. In this tutorial, we'll show you how to deploy a Wagtail blog to AWS Lambda using Zappa - a tool that packages and deploys Django/WSGI applications as serverless functions with minimal configuration. With this serverless setup, AWS manages the underlying infrastructure for you: your application can scale automatically, you only pay for the resources used when requests are processed, and there are no servers to patch, monitor, or maintain. We'll go through the complete deployment process step by step. By the end of this tutorial you will have a fully functional Wagtail blog running on AWS Lambda, backed by an external PostgreSQL database and Amazon S3 for media file storage.