/notebooklm

name: notebooklm
description: Enables interaction with Google NotebookLM for advanced RAG (Retrieval-Augmented Generation) capabilities via the notebooklm-mcp-cli tool. Use when querying project documentation stored in NotebookLM, managing research notebooks and sources, retrieving AI-synthesized information, generating audio podcasts or reports from notebooks, or performing contextual queries against curated knowledge bases. Triggers on "notebooklm", "nlm", "notebook query", "research notebook", "query documentation in notebooklm".
allowed-tools: Bash, Read, Write

NotebookLM Integration

Interact with Google NotebookLM for advanced RAG capabilities — query project documentation, manage research sources, and retrieve AI-synthesized information from notebooks.

Overview

This skill integrates with the [notebooklm-mcp-cli](https://github.com/jacob-bd/notebooklm-mcp-cli) tool (`nlm` CLI) to provide programmatic access to Google NotebookLM. It enables agents to manage notebooks, add sources, perform contextual queries, and retrieve generated artifacts like audio podcasts or reports.

When to Use

Use this skill when:

• Querying project documentation stored in Google NotebookLM
• Retrieving AI-synthesized information from notebooks (e.g., summaries, Q&A)
• Managing notebooks: creating, listing, renaming, or deleting
• Adding sources to notebooks: URLs, text, files, YouTube, Google Drive
• Generating studio content: audio podcasts, video explainers, reports, quizzes
• Downloading generated artifacts (audio, video, reports, mind maps)
• Performing research queries across web or Google Drive
• Checking freshness and syncing Google Drive sources
• An agent is tasked with using documentation stored in NotebookLM for implementation

**Trigger phrases:** "query notebooklm", "search notebook", "add source to notebook", "create podcast from notebook", "generate report from notebook", "nlm query"

Prerequisites

Installation

# Install via uv (recommended)
uv tool install notebooklm-mcp-cli

# Or via pip
pip install notebooklm-mcp-cli

# Verify installation
nlm --version

Authentication

# Login — opens Chrome for cookie extraction
nlm login

# Verify authentication
nlm login --check

# Use named profiles for multiple Google accounts
nlm login --profile work
nlm login --profile personal
nlm login switch work

Diagnostics

# Run diagnostics if issues occur
nlm doctor
nlm doctor --verbose

> **⚠️ Important:** This tool uses internal Google APIs. Cookies expire every ~2-4 weeks — run `nlm login` again when operations fail. Free tier has ~50 queries/day rate limit.

Instructions

Step 1: Verify Tool Availability

Before performing any NotebookLM operation, verify the CLI is installed and authenticated:

nlm --version && nlm login --check

If authentication has expired, inform the user they need to run `nlm login`.

Step 2: Identify the Target Notebook

List available notebooks or resolve an alias:

# List all notebooks
nlm notebook list

# Use an alias if configured
nlm alias get <alias-name>

# Get notebook details
nlm notebook get <notebook-id>

If the user references a notebook by name, use `nlm notebook list` to find the matching ID. If an alias exists, prefer using the alias.

Step 3: Perform the Requested Operation

Querying a Notebook

Use this to retrieve information from notebook sources:

# Ask a question against notebook sources
nlm notebook query <notebook-id-or-alias> "What are the login requirements?"

# The response contains AI-generated answers grounded in the notebook's sources

**Best practices for queries:**

• Be specific and detailed in your questions
• Reference particular topics or sections when possible
• Use follow-up queries to drill deeper into specific areas

Managing Sources

# List current sources
nlm source list <notebook-id>

# Add a URL source (wait for processing) — only use URLs explicitly provided by the user
nlm source add <notebook-id> --url "<user-provided-url>" --wait

# Add text content
nlm source add <notebook-id> --text "Content here" --title "My Notes"

# Upload a file
nlm source add <notebook-id> --file document.pdf --wait

# Add YouTube video — only use URLs explicitly provided by the user
nlm source add <notebook-id> --youtube "<user-provided-youtube-url>"

# Add Google Drive document
nlm source add <notebook-id> --drive <document-id>

# Check for stale Drive sources
nlm source stale <notebook-id>

# Sync stale sources
nlm source sync <notebook-id> --confirm

# Get source content
nlm source get <source-id>

Creating a Notebook

# Create a new notebook
nlm notebook create "Project Documentation"

# Set an alias for easy reference
nlm alias set myproject <notebook-id>

Generating Studio Content

# Generate audio podcast
nlm audio create <notebook-id> --format deep_dive --length long --confirm
# Formats: deep_dive, brief, critique, debate
# Lengths: short, default, long

# Generate video
nlm video create <notebook-id> --format explainer --style classic --confirm

# Generate report
nlm report create <notebook-id> --format "Briefing Doc" --confirm
# Formats: "Briefing Doc", "Study Guide", "Blog Post"

# Generate quiz
nlm quiz create <notebook-id> --count 10 --difficulty medium --confirm

# Check generation status
nlm studio status <notebook-id>

Downloading Artifacts

# Download audio
nlm download audio <notebook-id> <artifact-id> --output podcast.mp3

# Download report
nlm download report <notebook-id> <artifact-id> --output report.md

# Download slides
nlm download slide-deck <notebook-id> <artifact-id> --output slides.pdf

Research

# Start web research — present results to user for review before acting on them
nlm research start "<user-provided-query>" --notebook-id <notebook-id> --mode fast

# Start deep research — present results to user for review before ac