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NotebookLM MCP

MCP server for NotebookLM - Let your AI agents (Claude Code, Codex) research documentation directly with grounded, citation-backed answers from Gemini. Persistent auth, library management, cross-client sharing. Zero hallucinations, just your knowledge base. observed · 2026-08-28

github.com/PleasePrompto/notebooklm-mcp · TypeScript · MIT (permissive) observed · 2026-08-28

Health v2 · maintenance only

65/100

  • Activity 80
  • Release rhythm 69
  • Longevity 22
How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.

  • gap_med: 35
  • age_days: 321
  • days_rel: 124
  • days_push: 124
  • n_releases_24m: 4

Full methodology

Adoption not part of the score

3350 stars · 476 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

An MCP server and Claude Code skill that lets AI coding agents chat directly with Google NotebookLM notebooks, returning source-grounded, citation-backed answers from Gemini based only on the user's uploaded documents. It provides browser automation, notebook library management, persistent authentication, source ingestion, and audio overview generation over stdio and Streamable-HTTP transports.

Use cases

  • query my uploaded documents from claude code with citation-backed answers
  • connect an mcp client to google notebooklm notebooks
  • reduce hallucinations by grounding coding agent answers in my own docs
  • ingest sources into notebooklm and generate audio overviews programmatically
  • manage a library of notebooklm notebooks with persistent login
  • ask questions about my project documentation without copy-pasting into a browser

When to choose

  • you already use Claude Code or another MCP client and want NotebookLM as a grounded knowledge source
  • you want answers restricted to your uploaded documents with citations instead of keyword search over local files
  • you prefer NotebookLM's Gemini-based synthesis over building and maintaining a local RAG pipeline
  • you need to automate notebook chat, source ingestion, or audio overview creation

When to avoid

  • you need a fully offline or self-hosted RAG solution without a Google account
  • you want to use the skill inside the Claude Code web UI, which lacks the network access browser automation requires
  • you are not comfortable with browser automation against the NotebookLM web interface, which may break if Google changes it
  • you need a general-purpose web search or public-internet question answering rather than answers from your own corpus

Facets

service · maturity active

mcp rag agent-framework browser-extension large-language-models developer-tools artificial-intelligence python cli notebooklm google-gemini claude-code browser-automation citation-backed-answers knowledge-base source-grounded persistent-authentication audio-overviews stdio-transport streamable-http retrieval-augmented-generation nodejs docker

2 sources

Member repositories

RepositoryRoleHealth v2
PleasePrompto/notebooklm-mcpmain65
PleasePrompto/notebooklm-skillplugin48

For agents

markdown · JSON · MCP: product_card(name="PleasePrompto/notebooklm-mcp")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem