Packages
Jupyter AI is a JupyterLab extension that integrates agentic AI into computational notebooks, enabling collaboration with frontier AI agents through a native chat UI with file and command execution capabilities.
Install it if you use JupyterLab and want AI agent collaboration; the modular design means you only pay for what you use.
Provides a JupyterLab extension that integrates Agent Client Protocol (ACP) agents as AI personas, enabling developers to wrap external ACP-compliant tools as chat assistants with file and terminal capabilities.
Install only if you have JupyterLab >= 4.0.0 and plan to use at least one ACP agent; each persona requires its own external CLI tool installed separately, which is…
Provides default chat commands for Jupyter AI, including file attachment and persona management within JupyterLab.
Jupyter AI Magics provides a JupyterLab extension that integrates AI agents into computational notebooks through a chat interface, enabling agents to read files, run commands, and interact with notebooks via the Agent Client Protocol.
Provides the foundational infrastructure for managing and registering AI personas (custom chat assistants) in Jupyter AI environments, including base classes, lifecycle management, and automatic discovery via entry points.
Provides the core message routing layer for Jupyter AI, automatically detecting chat sessions and routing messages to registered callbacks based on message type.
A Jupyter Server extension that exposes file system, notebook, Git, and code execution tools for AI agents to programmatically interact with notebooks and repositories.
A JupyterLab extension that adds archive creation, download, and extraction capabilities directly in the file browser, supporting zip, tar.gz, tar.bz2, and tar.xz formats.
Install it if you regularly need to move folders in and out of Jupyter.
A Jupyter Notebook and JupyterLab extension that automatically formats Python code cells using Black after they are run.
However, note that the project is dormant (last release 2024-08-30); if you need active maintenance or encounter compatibility issues with newer versions, you may…
Renders Bokeh visualizations directly within Jupyter notebooks and JupyterLab, enabling interactive plots and dashboards in notebook cells.
Jupyter Book converts Markdown files and Jupyter notebooks into publication-quality books and documents, executing embedded code cells and generating both interactive web books and PDFs.
Install it if you need to publish computational content as a polished book or document.
Provides CLI and Python tools to build, develop, and watch JupyterLab extensions, compiling JavaScript assets and managing their installation into Jupyter environments.
Install it if you are building or developing JupyterLab extensions; it is not useful for end users of Jupyter.
Caches Jupyter notebook execution outputs to avoid re-running notebooks with deterministic outputs, enabling fast rebuilds of documentation and notebooks that depend on long-running computations.
Implements the Jupyter protocol and provides client and kernel management APIs for launching, communicating with, and managing Jupyter kernels.
Install it if you are building Jupyter frontends, managing kernels programmatically, or integrating interactive computation into applications.
Adds real-time collaborative editing to JupyterLab and Jupyter Notebook 7+, allowing multiple users to work on the same notebook simultaneously with synchronized changes.
Install it if you need multi-user editing; skip it if you work alone or use external version control for notebooks.
Adds real-time collaboration UI elements to JupyterLab and Jupyter Notebook 7+, enabling multiple users to work together on notebooks with synchronized editing.
Jupyter Console is a terminal-based frontend for Jupyter kernels, allowing interactive console-based interaction with non-Python kernels like Julia and R.
Provides common utilities, API compatibility shims, and test helpers for jupyter-contrib projects, smoothing over differences in Jupyter notebook versions.
Adds a collection of browser-based extensions to Jupyter notebooks, mostly written in JavaScript, that enhance notebook functionality with features loaded locally in the browser.
However, dormant maintenance (last release 2022-11-15) and the community-maintained status mean you should verify that the specific extensions you need work with your…
Provides base application classes and configuration infrastructure that Jupyter projects inherit from, handling core functionality like paths and traits management.
Jupyter Dash lets you develop and run Plotly Dash web applications interactively within Jupyter notebooks and compatible environments, rendering the app output directly in the notebook cell.
Adds real-time collaborative editing to JupyterLab and Jupyter Notebook 7+ using shared Y documents, enabling multiple users to work on the same notebook simultaneously.
Install it if your workflow involves multiple users editing notebooks together; skip it if you work alone or prefer file-based collaboration.
Jupyter Events provides an event system for Jupyter applications and extensions to emit and listen to structured events describing application state changes and user actions.
Install it if you are building or extending Jupyter applications that need to emit or consume events.
A Jupyter notebook extension that highlights all instances of a selected word across the notebook, with configurable scope (current cell or all cells) and visual styling options.
Adds a WebSocket-based HTTP proxy endpoint to Jupyter notebook servers, enabling cross-domain HTTP communication from browsers to localhost that would otherwise be blocked.
Connects to live Jupyter Kernels over HTTP and WebSocket to execute code remotely, and provides an interactive console (REPL) for kernel interaction.
Jupyter Kernel Gateway is a web server that exposes Jupyter kernels over HTTP and WebSocket, enabling remote code execution and kernel management without a notebook interface.
jupyter-leaflet provides interactive map widgets for Jupyter notebooks and JupyterLab, bridging Jupyter and Leaflet.js to render geospatial data and controls directly in notebook cells.
Bridges Language Server Protocol servers to Jupyter Notebook and Lab via WebSocket, enabling real-time code intelligence features like completion and diagnostics in the notebook editor.
An MCP server that exposes Jupyter notebooks and code execution to AI agents and clients, enabling real-time notebook management, cell execution, and sandbox-backed code runs across local and cloud environments.
Exposes JupyterLab commands as MCP (Model Context Protocol) tools, enabling external AI agents and clients to trigger notebook operations, file management, and kernel control through a standardized protocol.
Provides enhanced Jupyter representation capabilities through proxy objects, enabling Apache Arrow-based serialization for pandas DataFrames and Series, with pickle fallback for generic Python objects.
Provides a web-based graphical interface for enabling, disabling, and configuring Jupyter notebook extensions (nbextensions) without editing configuration files directly.
Programmatically interact with live Jupyter notebooks over WebSocket, adding and executing cells, and reading their outputs without running a kernel directly.
Provides build tools and utilities for packaging Jupyter Python projects that require pre-build steps, including JavaScript compilation and asset management.
Jupyter Server provides the backend services, APIs, and REST endpoints that power Jupyter web applications like Jupyter Notebook, JupyterLab, and Voilà.
A JupyterLab extension that moves document state to the server, enabling real-time collaboration, automatic saving, and optional off-disk output storage for improved performance.
A Jupyter Server extension that provides a File ID service for tracking and managing file identities within Jupyter environments.
However, the aging maintenance status (last release 707 days ago, minimal repository activity) suggests limited ongoing development—install only if the feature is…
Exposes Python functions as tools to MCP clients via a Jupyter Server extension, enabling AI assistants and other MCP-compatible applications to call registered functions through an HTTP endpoint.
Jupyter Server Proxy runs external processes (RStudio, Shiny, PostgreSQL, Code Server, etc.) alongside your Jupyter server and proxies authenticated web access to them through paths like `/rstudio`.