RRepoGEO

REPOGEO REPORT · LITE

jupyterlab/jupyter-ai

Default branch main · commit 69aefb33 · scanned 5/24/2026, 3:06:51 AM

GitHub: 4,241 stars · 496 forks

AI VISIBILITY SCORE
79 /100
Needs work
Category recall
2 / 2
Avg rank #1.0 when recommended
Rule findings
2 pass · 0 warn · 0 fail
Objective metadata checks
AI knows your name
1 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface jupyterlab/jupyter-ai, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highreadme#1
    Reposition README opening to highlight unique JupyterLab integration

    Why:

    CURRENT
    Jupyter AI brings agentic AI to JupyterLab. It provides a native chat UI where you can collaborate with frontier AI agents — including Claude, Codex, GitHub Copilot, Gemini, Goose, Kiro, Mistral Vibe, and OpenCode — all integrated through the Agent Client Protocol (ACP).
    COPY-PASTE FIX
    Jupyter AI brings agentic AI directly into JupyterLab, providing a native chat UI where you can collaborate with frontier AI agents. It deeply integrates with your computational notebooks, leveraging Jupyter's unique features like magic commands (`%%ai`, `%ai`) for contextual interaction within cells. Agents — including Claude, Codex, GitHub Copilot, Gemini, Goose, Kiro, Mistral Vibe, and OpenCode — are all integrated through the Agent Client Protocol (ACP).
  • mediumtopics#2
    Expand repository topics with specific AI/LLM terms

    Why:

    CURRENT
    acp, agents, jupyter, jupyterlab, jupyterlab-extension
    COPY-PASTE FIX
    acp, agents, jupyter, jupyterlab, jupyterlab-extension, llm, large-language-models, ai-agents, notebook-ai, data-science-ai, generative-ai
  • lowabout#3
    Refine the 'About' description for deeper integration

    Why:

    CURRENT
    An open source extension that connects AI agents to computational notebooks in JupyterLab.
    COPY-PASTE FIX
    An open source extension that deeply integrates AI agents and large language models directly into computational notebooks within JupyterLab, leveraging native features for interactive data analysis.

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
2 / 2
100% of queries surface jupyterlab/jupyter-ai
Avg rank
#1.0
Lower is better. #1 = top recommendation.
Share of voice
11%
Of all named tools, what % are you?
Top rival
langchain-ai/langchain
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. langchain-ai/langchain · recommended 1×
  2. ipython/ipython · recommended 1×
  3. run-llama/llama_index · recommended 1×
  4. OpenAI API · recommended 1×
  5. Google · recommended 1×
  • CATEGORY QUERY
    How can I integrate AI agents into my computational notebooks for interactive data analysis?
    you: #1
    AI recommended (in order):
    1. Jupyter AI (jupyterlab/jupyter-ai) ← you
    2. LangChain (langchain-ai/langchain)
    3. IPython (ipython/ipython)
    4. LlamaIndex (run-llama/llama_index)
    5. OpenAI API
    6. Google
    7. Anthropic
    8. Panel (holoviz/panel)
    9. Streamlit (streamlit/streamlit)
    10. AutoGPT (Significant-Gravitas/AutoGPT)
    11. BabyAGI (yoheinakajima/babyagi)
    12. Hugging Face Transformers (huggingface/transformers)
    13. Gradio (gradio-app/gradio)
    Show full AI answer
  • CATEGORY QUERY
    What are good tools for collaborating with AI agents on data science projects in a notebook?
    you: #1
    AI recommended (in order):
    1. Jupyter AI (jupyterlab/jupyter-ai) ← you
    2. GitHub Copilot
    3. Code Interpreter
    4. Google Colaboratory
    5. Databricks Assistant
    6. Deepnote
    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    pass

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of jupyterlab/jupyter-ai?
    pass
    AI did not name jupyterlab/jupyter-ai — likely talking about a different project

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts jupyterlab/jupyter-ai in production, what risks or prerequisites should they evaluate first?
    pass
    AI named jupyterlab/jupyter-ai explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo jupyterlab/jupyter-ai solve, and who is the primary audience?
    pass
    AI did not name jupyterlab/jupyter-ai — likely talking about a different project

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

Drop this badge into the README of jupyterlab/jupyter-ai. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
[![RepoGEO](https://repogeo.com/badge/jupyterlab/jupyter-ai.svg)](https://repogeo.com/en/r/jupyterlab/jupyter-ai)
HTML
<a href="https://repogeo.com/en/r/jupyterlab/jupyter-ai"><img src="https://repogeo.com/badge/jupyterlab/jupyter-ai.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

jupyterlab/jupyter-ai — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite