GitHub topic

jupyter GitHub repositories

Explore 11 tracked GitHub repositories tagged jupyter. Compare their recorded star activity and implementation languages, then follow related topics to find other projects.

Snapshot: 2026-10-28. The collection gained 6 stars since the previous daily snapshot.

Tracked repositories: 11
Total stars: 41,444
Stars gained · 7 days: +61
Stars gained · 30 days: +279

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Star activity for jupyter repositories on this page
Repository	Total stars	Today	7 days	30 days
ruc-datalab/DeepAnalyze	4.8K	+3	+20	+101
kubeflow/kubeflow	15.9K	+2	+16	+60
jupyterlab/jupyter-ai	4.4K	+1	+7	+19
datalayer/jupyter-mcp-server	1.3K	+0	+4	+26
microsoft/vscode-jupyter	1.5K	+0	+4	+8

Explore repositories

Showing 1–11 of 11 tracked repositories.

ruc-datalab/DeepAnalyze

DeepAnalyze is the first agentic LLM for autonomous data science. 🎈你的AI数据分析师，自动分析大量数据，一键生成专业分析报告！

kubeflow/kubeflow

The Cloud Native AI Platform

★ 15.9K+2 todayUnknown

ai machine-learning

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jupyterlab/jupyter-ai

An open source extension that connects AI agents to computational notebooks in JupyterLab.

★ 4.4K+1 todayPython

agents jupyter

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datalayer/jupyter-mcp-server

🪐 🔧 Model Context Protocol (MCP) Server for Jupyter.

★ 1.3K+0 todayPython

ai mcp

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microsoft/vscode-jupyter

VS Code Jupyter extension

★ 1.5K+0 todayTypeScript

machine-learning vscode

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OSGeo/grass

GRASS - free and open-source geospatial processing engine

ml-tooling/best-of-jupyter

🏆 A ranked list of awesome Jupyter Notebook, Hub and Lab projects (extensions, kernels, tools). Updated weekly.

Deepnote is a drop-in replacement for Jupyter with an AI-first design, sleek UI, new blocks, and native data integrations. Use Python, R, and SQL locally in your favorite IDE, then scale to Deepnote cloud for real-time collaboration, Deepnote agent, and deployable data apps. https://deepnote.com/

★ 3.0K+0 todayTypeScript

machine-learning python

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microsoft/responsible-ai-toolbox

Responsible AI Toolbox is a suite of tools providing model and data exploration and assessment user interfaces and libraries that enable a better understanding of AI systems. These interfaces and libraries empower developers and stakeholders of AI systems to develop and monitor AI more responsibly, and take better data-driven actions.