nlp

Natural language processing tutorials covering text analysis and language tasks in Python.

Build an MCP Server in Python (FastMCP, Step by Step)

Write a useful function once and every AI assistant should be able to call it: Claude Desktop, your editor, your own agent loop. That is exactly what you get when you build MCP server tooling around code you already trust. In this workshop we wrap the access-log parser and the bookmark Application Programming Interface (API) from earlier posts into one FastMCP server with three tools, a resource, and a prompt, all offline. “Write the tool once, then let every assistant ... Read More

Model Context Protocol (MCP): Connect Your AI to Anything

The Model Context Protocol is a single, open way for an AI app to talk to outside tools, files, and data, so you stop writing custom glue for every new integration. Think of it like the USB port on your laptop. Before USB, every device had its own weird plug. After USB, one shape fits the mouse, the drive, the keyboard. MCP does the same thing for AI: one protocol, and any tool that speaks it plugs straight in. You ... Read More

Jupyter Notebook and Google Colab: The Data Science Setup

A Jupyter notebook lets you write Python in small cells and run them one at a time, with each result appearing right under its code instead of at the end of a whole file. That tight feedback loop is why data science happens in notebooks. This post covers cells and the kernel, installing JupyterLab, Google Colab, magics, inline plots, and the out-of-order trap that bites almost every beginner. “A notebook is a lab bench, not a factory floor. You experiment ... Read More