mljar/mercury

Impress your boss and turn a Jupyter notebook into a beautiful, shareable web app — no callbacks, no frontend, no rewrite.

What it solves

Mercury simplifies the process of turning Python notebooks into interactive web applications. It eliminates the need to rewrite notebook code into a separate script (like an app.py file) or manage complex UI callbacks, allowing data scientists and AI researchers to share their work with non-technical users as a polished, data-rich app.

How it works

Mercury transforms .ipynb files directly into web apps. It uses a reactive notebook model where changing a widget value automatically triggers the re-execution of the cells below it. The framework provides a collection of predefined widgets (such as chat interfaces and inputs) and a standalone server to host these notebooks as apps. It also includes a JupyterLab extension for live previews during development.

Who it’s for

It is designed for users who have existing Jupyter notebooks containing data analysis, AI agents, or reports and want to deploy them as interactive tools for non-programmers without changing their development workflow.

Highlights

  • Reactive Execution: No callbacks or event handlers; widget interactions simply fire cell re-execution.
  • Notebook-First: The notebook remains the source of truth and stays runnable in Jupyter.
  • AI-Ready: Includes specialized widgets for building chat bots and AI agents.
  • Deployment Flexibility: Can be deployed via a standalone server, Docker, or a managed cloud service.
  • Access Control: Supports password protection for hosted apps.

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