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.

v1.7.5 — production-grade, batch-tested on overnight runs of 1 000+ questions. New: batch_to_vault is now a first-class MCP tool (no HTTP server required) on top of the existing POST /batch-to-vault endpoint. See RTFM integration for the full pattern. Compare with PleasePrompto/notebooklm-mcp v2.0.0 to see when this project is the right pick (REST API, full Studio, auto-reauth) and when the MCP-only upstream is.

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

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

Integration Options

• MCP Protocol — Claude Code, Cursor, Codex, any MCP client

• 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 npm run setup-auth once to log into Google. 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"]
    }
  }
}

Then say: "Log me in to NotebookLM" → Chrome opens → log in with Google.

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 notebooklm-mcp

# Authenticate via noVNC
# 1. Open http://localhost:6080/vnc.html
# 2. Run: curl -X POST http://localhost:3000/setup-auth -d '{"show_browser":true}'
# 3. Login to Google in the VNC window

See Docker Guide for NAS deployment (Synology, QNAP).

Documentation

Full docs site: https://roomi-fields.github.io/notebooklm-mcp/ · OpenAPI 3.1 spec

Roadmap

See ROADMAP.md for planned features and version history.

Latest releases:

• v1.7.5 — Three end-user bugs fixed: (1) /plugin marketplace update roomi-fields + /reload-plugins now actually upgrades the running MCP (npx pin in plugin.json); (2) list_notebooks_from_nblm no longer hardcodes "Notebook" as title — id-based scrape returns real names; (3) get_health.current_account no longer returns a stale email after re_auth

• v1.7.4 — Expose create_notebook and delete_notebooks_from_nblm as MCP tools (handlers existed but lacked a tool definition + dispatch case); 30/30 alignment audit passes

• v1.7.3 — Fix: list_notebooks_from_nblm MCP tool was declared but unreachable (missing dispatch case) — now resolves correctly

• v1.7.2 — Claude Code plugin manifest (.claude-plugin/plugin.json) + cross-file version sync script enforced in CI; README "Install via Claude Code marketplace" one-liner

• v1.7.0 — batch_to_vault exposed as a first-class MCP tool (parity with the HTTP endpoint, no localhost server required); shared runBatchToVault helper deduplicates the loop across both transports

• v1.6.0 — /batch-to-vault endpoint + RTFM integration (nblm-answer-v1 JSON Schema published at schemas.roomi-fields.com/nblm-answer-v1.json) for caching NotebookLM answers as a searchable markdown vault

• v1.5.9 — Restore mcpName field for MCP Registry npm-package ownership verification

• v1.5.8 — NotebookLM 2026 UI adaptations (icon-label sanitization, Discussion-panel recovery, count-based source detection) — PR #5 by @KhizarJamshaidIqbal

• v1.5.7 — Citation extraction selector fix (.highlighted) and Docker multi-stage build — PR #1 by @JulienCANTONI

• v1.5.6 — Citation extraction major rewrite (97% success rate), browser-verified auth at startup, profile auto-sync

• v1.5.5 — Multi-account state-path bug fix, Windows startup scripts, hidden-window MCP proxy

• v1.5.4 — Mid-session auto-reauth with stored credentials, TOTP support

• v1.5.3 — Docker deployment with noVNC for visual authentication + NAS support (Synology, QNAP)

• v1.5.2 — Notebook scraping from NotebookLM + Bulk delete + Bug fixes

• v1.5.1 — Multilingual UI support (FR/EN) with i18n selector system + E2E tests (76 tests)

• v1.5.0 — Complete Studio content generation (video, infographic, presentation, data_table) + Notes management + Delete sources

• v1.4.0 — Content management (sources, audio, generation) + Multi-account

Not yet implemented:

• Discover sources (Web/Drive search with Fast/Deep modes)

• Edit notes (create, delete, and convert are implemented)

Disclaimer

This tool automates browser interactions with NotebookLM. Use a dedicated Google account for automation. CLI tools like Claude Code can make mistakes — always review changes before deploying.

See full Disclaimer below.

Contributing

Found a bug? Have an idea? Open an issue or submit a PR!

See CONTRIBUTING.md for guidelines.

License

MIT — Use freely in your projects. See LICENSE.

Author

Romain Peyrichou — @roomi-fields

About browser automation: While I've built in humanization features (realistic typing speeds, natural delays, mouse movements), I can't guarantee Google won't detect or flag automated usage. Use a dedicated Google account for automation.

About CLI tools and AI agents: CLI tools like Claude Code, Codex, and similar AI-powered assistants are powerful but can make mistakes:

• Always review changes before committing or deploying

• Test in safe environments first

• Keep backups of important work

• AI agents are assistants, not infallible oracles

I built this tool for myself and share it hoping it helps others, but I can't take responsibility for any issues that might occur. Use at your own discretion.

Built with frustration about hallucinated APIs, powered by Google's NotebookLM

⭐ Star on GitHub if this saves you debugging time!