RRepoGEO

REPOGEO REPORT · LITE

PleasePrompto/notebooklm-mcp

Default branch main · commit 50b3e7f6 · scanned 5/19/2026, 1:47:02 PM

GitHub: 2,476 stars · 338 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
    Reposition README H1 and opening paragraph

    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. Two transports are supported: `stdio` (default) and Streamable-HTTP. v2.0.0 is the current line; v1 is no longer supported.
    COPY-PASTE FIX
    # NotebookLM Model Context Protocol (MCP) Server: Grounded AI Agent Interaction

This is the Model Context Protocol (MCP) server for Google NotebookLM, designed to empower AI agents (like Claude Code or Codex) with grounded, citation-backed answers directly from your knowledge base. It drives a real Chrome instance via Patchright for stealthy, persistent interaction, enabling agents to chat against notebooks, ingest sources, generate audio overviews, and read DOM-level citations. Achieve zero hallucinations by connecting your AI agents to NotebookLM's robust information retrieval.
  • hightopics#2
    Add specific topics to improve categorization

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    notebooklm, ai-agents, generative-ai, rag, citation, grounded-ai, model-context-protocol, typescript, node, chrome-automation
  • mediumhomepage#3
    Add project 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
LangChain
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain · recommended 1×
  2. Pinecone · recommended 1×
  3. Chroma · recommended 1×
  4. Weaviate · recommended 1×
  5. LlamaIndex · recommended 1×
  • CATEGORY QUERY
    How to provide AI agents with grounded, citation-backed answers from a knowledge base?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. Pinecone
    3. Chroma
    4. Weaviate
    5. LlamaIndex
    6. Haystack
    7. Elasticsearch
    8. FAISS
    9. OpenAI Embeddings
    10. Cohere Embeddings
    11. Annoy
    12. Scikit-learn Nearest Neighbors

    AI recommended 12 alternatives but never named PleasePrompto/notebooklm-mcp. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What solutions exist for AI agents to browse web content and get verifiable citations?
    you: not recommended
    AI recommended (in order):
    1. SerpApi
    2. Google Search API
    3. LangChain (langchain-ai/langchain)
    4. LlamaIndex (run-llama/llama_index)
    5. Playwright (microsoft/playwright)
    6. Puppeteer (puppeteer/puppeteer)
    7. Beautiful Soup (crummy/beautifulsoup4)
    8. Cheerio (cheeriojs/cheerio)
    9. Apify
    10. Scrapy (scrapy/scrapy)
    11. You.com
    12. Perplexity AI

    AI recommended 12 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 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?

  • 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 named PleasePrompto/notebooklm-mcp explicitly

    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