系统运行机制 Jupyter MCP 服务器采用后台服务的运行模式，它不提供独立的用户界面，而是集成在 JupyterLab 或 Jupyter Notebook 的运行环境中。

随着 2019 年 VS Code Python 插件的最新发布，VS Code 已经提供了对 Jupyter Notebook 的本地支持，也就是可以在不运行 Jupyter Notebook 的情况下在笔记本上工作。

Jupyter Notebook installation and setup The easiest way to create and work with Jupyter Notebooks for Python is to set up an instance of the Anaconda distribution of Python.

In the regular monthly update to Python tooling for Visual Studio Code, Microsoft announced an improved setup experience for Jupyter notebooks, along with new inlay type hints for the Pylance language ...

There's nothing quite like running Python code on your self-hosted Jupyter Notebook server ...

Faster start-up times for the Jupyter Notebook editor and associated server highlight the February update to the wildly popular Python Extension for Visual Studio Code.

Jupyter Notebook is not a full-blown development environment for Python. Many of the features you would expect to find in an IDE—e.g., interactive debugging, code completion, and module ...

Image: Jupyter Notebook Jupyter is a browser-based, open-source data science notebook tool that supports Python, Julia, and other dynamic programming languages such as R, Scilab and Octane.

Because of the client/server architecture, it is very simple to share notebooks with other users. You can — in theory — use Jupyter for anything you could use Python for.

For instance, PyXLL-Jupyter can integrate data from your Excel workbook into a Jupyter Notebook using a single command. This enables you to analyze massive datasets quickly.