RRepoGEO

REPOGEO REPORT · LITE

PleasePrompto/notebooklm-mcp

Default branch main · commit 50b3e7f6 · scanned 6/30/2026, 11:12:11 PM

GitHub: 2,895 stars · 406 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
28 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
2 / 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 PleasePrompto/notebooklm-mcp, 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
    Clarify README's opening to emphasize AI agent research

    Why:

    CURRENT
    # NotebookLM MCP Server

MCP server for Google NotebookLM. It drives a real Chrome via Patchright (stealth + persistent fingerprint) so an agent can chat against a notebook, ingest sources, generate audio overviews, and read DOM-level citations.
    COPY-PASTE FIX
    # NotebookLM MCP Server

The **NotebookLM Model Context Protocol (MCP) Server** enables AI agents (like Claude Code, Codex) to research documentation directly within Google NotebookLM, providing grounded, citation-backed answers from Gemini. It drives a real Chrome via Patchright (stealth + persistent fingerprint) so agents can chat against a notebook, ingest sources, generate audio overviews, and read DOM-level citations, ensuring zero hallucinations and leveraging your knowledge base.
  • hightopics#2
    Add specific topics to improve categorization

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    notebooklm, ai-agents, llm-agents, knowledge-base, grounded-generation, citation-backed, web-scraping, browser-automation, gemini, claude-code, codex, model-context-protocol
  • mediumhomepage#3
    Set the repository homepage URL

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    https://modelcontextprotocol.io/

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
0 / 2
0% of queries surface PleasePrompto/notebooklm-mcp
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LlamaIndex
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. LlamaIndex · recommended 1×
  2. LangChain · recommended 1×
  3. Pinecone · recommended 1×
  4. Weaviate · recommended 1×
  5. Chroma · recommended 1×
  • CATEGORY QUERY
    How can I enable AI agents to research documentation with citation-backed, factual answers?
    you: not recommended
    AI recommended (in order):
    1. LlamaIndex
    2. LangChain
    3. Pinecone
    4. Weaviate
    5. Chroma
    6. Haystack
    7. OpenAI Assistants API
    8. Azure AI Search
    9. Azure OpenAI Service
    10. Google Cloud Vertex AI Search and Conversation

    AI recommended 10 alternatives but never named PleasePrompto/notebooklm-mcp. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools help AI agents browse web content and ingest sources for a custom knowledge base?
    you: not recommended
    AI recommended (in order):
    1. Beautiful Soup (beautifulsoup4/beautifulsoup4)
    2. Scrapy (scrapy/scrapy)
    3. Playwright (microsoft/playwright)
    4. Selenium (SeleniumHQ/selenium)
    5. LangChain (langchain-ai/langchain)
    6. LlamaIndex (run-llama/llama_index)
    7. Apache Nutch (apache/nutch)
    8. Puppeteer (puppeteer/puppeteer)

    AI recommended 8 alternatives but never named PleasePrompto/notebooklm-mcp. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    warn

    Suggestion:

  • 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 PleasePrompto/notebooklm-mcp?
    pass
    AI named PleasePrompto/notebooklm-mcp explicitly

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

  • If a team adopts PleasePrompto/notebooklm-mcp in production, what risks or prerequisites should they evaluate first?
    pass
    AI named PleasePrompto/notebooklm-mcp 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 PleasePrompto/notebooklm-mcp solve, and who is the primary audience?
    pass
    AI did not name PleasePrompto/notebooklm-mcp — 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?

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PleasePrompto/notebooklm-mcp — 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