NotebookLM REST API + MCP server

Automate Google NotebookLM at scale. 33-endpoint HTTP REST API for n8n / Zapier / Make / curl, plus an MCP server for Claude Code / Cursor / Codex. Citation-backed Q&A, full Studio generation (audio · video · infographic · report · presentation · data table), multi-account rotation with auto-reauth across personal and Google Workspace accounts.

v3.0.1 — major refactor: dual transport. The data plane now drives NotebookLM's internal batchexecute RPC API (the same one the web app calls) instead of scraping the DOM — immune to UI rebrands, 10-100× faster (list notebooks ~1 s vs ~30 s, generate a report ~13 s vs minutes), and more correct. The Playwright browser is kept as an automatic fallback (NOTEBOOKLM_TRANSPORT=dom forces it) plus login / auto-reauth, so nothing breaks if an internal endpoint shifts — both paths ship permanently for robustness. Adds 5 new tools: notebook sharing, study aids (flashcards / quiz), mind maps, source labels, and web research / source discovery. Still batch-tested on overnight runs of 1 000+ questions. See the changelog. Compare with PleasePrompto/notebooklm-mcp for when this project is the right pick (REST API, full Studio, auto-reauth).

Features

Q&A with Citations

• Ask questions to NotebookLM and get accurate, citation-backed answers
• Source citation extraction with 5 formats: none, inline, footnotes, json, expanded (97% excerpt success rate)
• Session management for multi-turn conversations with auto-reauth on session expiry

Content Generation

Generate multiple content types from your notebook sources:

Video Visual Styles: classroom, documentary, animated, corporate, cinematic, minimalist

Flashcards and quizzes are generated via generate_study_aid; mind maps via generate_mind_map. v3 also adds share_notebook, manage_labels, and research_sources (web/Drive source discovery) — see the changelog.

Content Download

• Download Audio — WAV audio files
• Download Video — MP4 video files
• Download Infographic — PNG image files
• Text-based content (report, presentation, data_table) is returned in the API response

Source Management

• Add sources: Files (PDF, TXT, DOCX), URLs, Text, YouTube videos, Google Drive
• List sources: View all sources in a notebook

Notebook Library

• Multi-notebook management with validation and smart selection
• Auto-discovery: Automatically generate metadata via NotebookLM queries
• Search notebooks by keyword in name, description, or topics
• Scrape notebooks: List all notebooks from NotebookLM with IDs and names
• Bulk delete: Delete multiple notebooks at once

Accounts & Localization

• Personal and Google Workspace accounts — recognizes both NotebookLM hosts (notebooklm.google.com and the notebook.google.com Workspace alias), so Workspace sessions authenticate cleanly instead of looping on "session expired"
• UI-language-aware — drives NotebookLM whether its interface is in English, French, German, or Japanese (en · fr · de · ja); add a language in a single JSON file

Integration Options

• MCP Protocol — Claude Code, Cursor, Codex, any MCP client
• Agent Skill — ships a bundled notebooklm skill (also standalone: roomi-fields/notebooklm-skill) that teaches the agent citation formats, the daily-quota-aware batch pattern, and when to use which transport
• HTTP REST API — n8n, Zapier, Make.com, custom integrations
• Docker — Isolated deployment with Docker or Docker Compose
• RTFM retrieval layer — /batch-to-vault writes citation-backed answers as markdown + JSON sidecars (nblm-answer-v1 schema), indexable by RTFM (FTS5 + semantic) for unlimited offline queries. Ideal for academic / SOTA workflows. Guide.

Quick Start

Option 0 — Claude Code marketplace (one-liner, recommended for Claude Code users)

The fastest way to get NotebookLM into Claude Code. Distributed via the roomi-fields/claude-plugins marketplace alongside RTFM (the retrieval companion — see RTFM integration guide):

/plugin marketplace add roomi-fields/claude-plugins
/plugin install notebooklm@roomi-fields

That registers the MCP server, runs npx -y @roomi-fields/notebooklm-mcp@<pinned-version> automatically (Node ≥ 18 required), and lets you upgrade with two commands when a new release ships: /plugin marketplace update roomi-fields then /reload-plugins. Then run npx -y -p @roomi-fields/notebooklm-mcp notebooklm-mcp-setup-auth once in a terminal to log into Google (a visible Chrome opens). To install RTFM at the same time: /plugin install rtfm@roomi-fields.

Option 1 — HTTP REST API (n8n, Zapier, Make, curl, any HTTP client)

git clone https://github.com/roomi-fields/notebooklm-mcp.git
cd notebooklm-mcp
npm install && npm run build
npm run setup-auth   # One-time Google login
npm run start:http   # Start REST API on port 3000

# Citation-backed Q&A, single curl, JSON response
curl -X POST http://localhost:3000/ask \
  -H 'Content-Type: application/json' \
  -d '{"question": "Summarize chapter 3", "notebook_id": "your-id", "source_format": "json"}'

The full surface is 33 documented endpoints — see the REST API reference. For overnight batches of 1 000+ questions, see the batch pattern.

Option 2 — MCP Mode (Claude Code, Cursor, Codex)

# Build (same package, MCP transport)
git clone https://github.com/roomi-fields/notebooklm-mcp.git
cd notebooklm-mcp
npm install && npm run build

# Claude Code
claude mcp add notebooklm node /path/to/notebooklm-mcp/dist/index.js

# Cursor — add to ~/.cursor/mcp.json
{
  "mcpServers": {
    "notebooklm": {
      "command": "node",
      "args": ["/path/to/notebooklm-mcp/dist/index.js"]
    }
  }
}

Log in once — in a terminal, not through the assistant. Run the interactive Google login as a command; a visible Chrome window opens, you sign in, and the saved session is then reused by the MCP server:

npm run setup-auth          # from a clone (Option 2 above)
notebooklm-mcp setup-auth   # from a global install (npm i -g @roomi-fields/notebooklm-mcp)

Do the login in a terminal rather than by asking the assistant "log me in": some stdio MCP clients (e.g. Claude Desktop) cap tool-call duration and cut off the up-to-10-minute interactive login before you can finish signing in (see issue #27).

Option 3 — Docker (NAS, server, headless)

# Build and run
docker build -t notebooklm-mcp .
docker run -d --name notebooklm-mcp -p 3000:3000 -p 6080:6080 -v notebooklm-data:/data note