NotebookLM CLI & MCP Server

Programmatic access to Google NotebookLM — via command-line interface (CLI) or Model Context Protocol (MCP) server.

Note: Tested with Pro/free and Google AI Ultra ($249/mo) tier accounts. May work with NotebookLM Enterprise accounts but has not been tested.

📺 Watch the Demos

Latest

Codex Setup + Cinematic Video & Slides

MCP Demos

General Overview	Claude Desktop	Perplexity Desktop	MCP Super Assistant

CLI Demos

CLI Overview	CLI, MCP & Skills	Setup, Doctor & mcpb	Infographics Support

Two Ways to Use

🖥️ Command-Line Interface (CLI)

Use nlm directly in your terminal for scripting, automation, or interactive use:

nlm notebook list                              # List all notebooks
nlm notebook create "Research Project"         # Create a notebook
nlm source add <notebook> --url "https://..."  # Add sources
nlm audio create <notebook> --confirm          # Generate podcast
nlm download audio <notebook> <artifact-id>    # Download audio file
nlm share public <notebook>                    # Enable public link

Run nlm --ai for comprehensive AI-assistant documentation.

🤖 MCP Server (for AI Agents)

Connect AI assistants (Claude, Gemini, Cursor, etc.) to NotebookLM:

# Automatic setup — picks the right config for each tool
nlm setup add claude-code
nlm setup add gemini
nlm setup add github-copilot
nlm setup add cursor
nlm setup add cline
nlm setup add antigravity

# Generate JSON config for any other tool
nlm setup add json

Then use natural language: "Create a notebook about quantum computing and generate a podcast"

Features

Capability	CLI Command	MCP Tool
List notebooks	nlm notebook list	notebook_list
Create notebook	nlm notebook create	notebook_create
Add Sources (URL, Text, Drive, File)	nlm source add	source_add
Query notebook (persists to web UI)	nlm notebook query	notebook_query
Create Studio Content (Audio, Video, etc.)	nlm studio create	studio_create
Revise slide decks	nlm slides revise	studio_revise
Download artifacts	nlm download <type>	download_artifact
Web/Drive research	nlm research start	research_start
Share notebook	nlm share public/invite	notebook_share_*
Sync Drive sources	nlm source sync	source_sync_drive
Batch operations	nlm batch query/create/delete	batch
Cross-notebook query	nlm cross query	cross_notebook_query
Pipelines (multi-step workflows)	nlm pipeline run/list	pipeline
Tag & smart select	nlm tag add/list/select	tag
Configure AI tools	nlm setup add/remove/list	—
Install AI Skills	nlm skill install/update	—
Diagnose issues	nlm doctor	—

📚 More Documentation:

• Getting Started — Install, login, agent setup, and migration from another NotebookLM MCP
• CLI Guide — Complete command reference
• MCP Guide — All 35 MCP tools with examples
• Authentication — Setup and troubleshooting
• Remote MCP — Web/mobile connector feasibility, security, and authentication limitations
• API Reference — Internal API docs for contributors

Important Disclaimer

This MCP and CLI use internal APIs that:

• Are undocumented and may change without notice
• Require cookie extraction from your browser (I have a tool for that!)

Use at your own risk for personal/experimental purposes.

Installation

🆕 Claude Desktop users: Download the extension (.mcpb file) → double-click → done! One-click install, no config needed.

Install from PyPI. This single package includes both the CLI and MCP server:

Using uv (Recommended)

uv tool install notebooklm-mcp-cli

Using uvx (Run Without Install)

uvx --from notebooklm-mcp-cli nlm --help
uvx --from notebooklm-mcp-cli notebooklm-mcp

Using pip

pip install notebooklm-mcp-cli

Using pipx

pipx install notebooklm-mcp-cli

After installation, you get:

• nlm — Command-line interface
• notebooklm-mcp — MCP server for AI assistants

<details> <summary>Alternative: Install from Source</summary>

# Clone the repository
git clone https://github.com/jacob-bd/notebooklm-mcp-cli.git
cd notebooklm-mcp

# Install with uv
uv tool install .

</details>

Upgrading

# Using uv
uv tool upgrade notebooklm-mcp-cli

# Using pip
pip install --upgrade notebooklm-mcp-cli

# Using pipx
pipx upgrade notebooklm-mcp-cli

After upgrading, restart your AI tool to reconnect to the updated MCP server:

• Claude Code: Restart the application, or use /mcp to reconnect
• Cursor: Restart the application
• Gemini CLI: Restart the CLI session

Upgrading from Legacy Versions

If you previously installed the separate CLI and MCP packages, you need to migrate to the unified package.

Step 1: Check What You Have Installed

uv tool list | grep notebooklm

Legacy packages to remove:

Package	What it was
notebooklm-cli	Old CLI-only package
notebooklm-mcp-server	Old MCP-only package

Step 2: Uninstall Legacy Packages

# Remove old CLI package (if installed)
uv tool uninstall notebooklm-cli

# Remove old MCP package (if installed)
uv tool uninstall notebooklm-mcp-server

Step 3: Reinstall the Unified Package

After removing legacy packages, reinstall to fix symlinks:

uv tool install --force notebooklm-mcp-cli

Why --force? When multiple packages provide the same executable, uv can leave broken symlinks after uninstalling. The --force flag ensures clean symlinks.

Step 4: Verify Installation

uv tool list | grep notebooklm

You should see only:

notebooklm-mcp-cli v0.2.0
- nlm
- notebooklm-mcp

Step 5: Re-authenticate

Your existing cookies should still work, but if you encounter auth issues:

nlm login

Note: MCP server configuration (in Claude Code, Cursor, etc.) does not need to change — the executable name notebooklm-mcp is the same.

Getting Started

If you are setting up the tool for the first time — or migrating from a browser-based NotebookLM MCP — see the Getting Started Guide. It covers install, login, agent registration, and a step-by-step migration path that avoids the "two NotebookLM servers registered" trap.

Uninstalling

To completely remove the MCP:

# Using uv
uv tool uninstall notebooklm-mcp-cli

# Using pip
pip uninstall notebooklm-mcp-cli

# Using pipx
pipx uninstall notebooklm-mcp-cli

# Remove cached auth tokens and data (optional)
rm -rf ~/.notebooklm-mcp-cli

Also remove from your AI tools:

nlm setup remove claude-code
nlm setup remove cursor
# ... or any configured tool

Authentication

Before using the CLI or MCP, you need to authenticate with NotebookLM:

CLI Authentication (Recommended)

# Auto mode: launches your browser, you log in, cookies extracted automatically
nlm login

# Check if already authenticated
nlm login --check

# Use a named profile (for multiple Google accounts)
nlm login --profile work
nlm login --profile personal

# Manual mode: import cookies from a file
nlm login --manual --file cookies.txt

# External CDP provider (e.g., OpenClaw-managed browser)
nlm login --provider openclaw --cdp-url http://127.0.0.1:18800

Profile management:

nlm login --check                    # Show current auth status
nlm login switch <profile>           # Switch the default profile
nlm login profile list               # List all profiles with email addresses
nlm login profile delete <profile>   # Delete a profile
nlm login profile rename <old> <new> # Rename a profile

Each profile gets its own isolated browser session, so you can be logged into multiple Google accounts simultaneously.

Standalone Auth Tool

If you only need the MCP server (not the CLI):

nlm login              # Auto mode (launches browser)
nlm login --manual     # Manual file mode

How it works: Auto mode launches a dedicated browser profile (supports Chrome, Arc, Brave, Edge, Chromium, and more), you log in to Google, and cookies are extracted automatically. Your login persists for future auth refreshes.

Prefer a specific browser? Set it with nlm config set auth.browser chromium (or brave, arc, edge, chrome, etc.). Falls back to auto-detection if the preferred browser is not found.

For detailed instructions and troubleshooting, see docs/AUTHENTICATION.md.

MCP Configuration

⚠️ Context Window Warning: This MCP provides 39 tools. Disable it when not using NotebookLM to preserve context. In Claude Code: @notebooklm-mcp to toggle.

Automatic Setup (Recommended)

Use nlm setup to automatically configure the MCP server for your AI tools — no manual JSON editing required:

# Add to any supported tool
nlm setup add claude-code
nlm setup add claude-desktop
nlm setup add gemini
nlm setup add github-copilot
nlm setup add cursor
nlm setup add windsurf

# Generate JSON config for any other tool
nlm setup add json

# Check which tools are configured
nlm setup list

# Diagnose installation & auth issues
nlm doctor

Install AI Skills (Optional)

Install the NotebookLM expert guide for your AI assistant to help it use the tools effectively. Supported for Cline, Antigravity, OpenClaw, Codex, OpenCode, Claude Code, and Gemini CLI.

# Install skill files
nlm skill install cline
nlm skill install openclaw
nlm skill install codex
nlm skill install antigravity

# Update skills
nlm skill update

Remove from a tool

nlm setup remove claude-code

Using uvx (No Install Required)

If you don't want to install the package, you can use uvx to run on-the-fly:

# Run CLI commands directly
uvx --from notebooklm-mcp-cli nlm setup add cursor
uvx --from notebooklm-mcp-cli nlm login

For tools that use JSON config, point them to uvx:

{
  "mcpServers": {
    "notebooklm-mcp": {
      "command": "uvx",
      "args": ["--from", "notebooklm-mcp-cli", "notebooklm-mcp"]
    }
  }
}

<details> <summary>Manual Setup (if you prefer)</summary>

Tip: Run nlm setup add json for an interactive wizard that generates the right JSON snippet for your tool.

Claude Code / Gemini CLI support adding MCP servers via their own CLI:

claude mcp add --scope user notebooklm-mcp notebooklm-mcp
gemini mcp add --scope user notebooklm-mcp notebooklm-mcp

Cursor / Windsurf resolve commands from your PATH, so the command name is enough:

{
  "mcpServers": {
    "notebooklm-mcp": {
      "command": "notebooklm-mcp"
    }
  }
}

Tool	Config Location
Cursor	~/.cursor/mcp.json
Windsurf	~/.codeium/windsurf/mcp_config.json

GitHub Copilot (VS Code workspace) uses .vscode/mcp.json with a top-level servers key:

{
  "servers": {
    "notebooklm-mcp": {
      "command": "notebooklm-mcp",
      "args": []
    }
  }
}

Claude Desktop may not resolve PATH — use the full path to the binary:

{
  "mcpServers": {
    "notebooklm-mcp": {
      "command": "/full/path/to/notebooklm-mcp"
    }
  }
}

Find your path with: which notebooklm-mcp

Tool	Config Location
Claude Desktop	~/Library/Application Support/Claude/claude_desktop_config.json
GitHub Copilot	.vscode/mcp.json

</details>

📚 Full configuration details: MCP Guide — Server options, environment variables, HTTP transport, and context window management. For Claude web/mobile and public deployment, read Remote MCP Deployment first.

What You Can Do

Simply chat with your AI tool (Claude Code, Cursor, Gemini CLI) using natural language. Here are some examples:

Research & Discovery

• "List all my NotebookLM notebooks"
• "Create a new notebook called 'AI Strategy Research'"
• "Start web research on 'enterprise AI ROI metrics' and show me what sources it finds"
• "Do a deep research on 'cloud marketplace trends' and import the top 10 sources"
• "Search my Google Drive for documents about 'product roadmap' and create a notebook"

Adding Content

• "Add this URL to my notebook: https://example.com/article"
• "Add this YouTube video about Kubernetes to the notebook"
• "Add my meeting notes as a text source to this notebook"
• "Import this Google Doc into my research notebook"

AI-Powered Analysis

• "What are the key findings in this notebook?"
• "Summarize the main arguments across all these sources"
• "What does this source say about security best practices?"
• "Get an AI summary of what this notebook is about"
• "Configure the chat to use a learning guide style with longer responses"

(All queries sent from CLI or MCP automatically persist in your NotebookLM web UI chat history!)

Content Generation

• "Create an audio podcast overview of this notebook in deep dive format"
• "Generate a video explainer with classic visual style"
• "Make a briefing doc from these sources"
• "Create flashcards for studying, medium difficulty"
• "Generate an infographic in landscape orientation with professional style"
• "Build a mind map from my research sources"
• "Create a slide deck presentation from this notebook"

Smart Management

• "Check which Google Drive sources are out of date and sync them"
• "Show me all the sources in this notebook with their freshness status"
• "Delete this source from the notebook"
• "Check the status of my audio overview generation"

Sharing & Collaboration

• "Show me the sharing settings for this notebook"
• "Make this notebook public so anyone with the link can view it"
• "Disable public access to this notebook"
• "Invite user@example.com as an editor to this notebook"
• "Add a viewer to my research notebook"

Pro tip: After creating studio content (audio, video, reports, etc.), poll the status to get download URLs when generation completes.

Authentication Lifecycle

Component	Duration	Refresh
Cookies	~2-4 weeks	Auto-refresh via headless browser (if profile saved)
CSRF Token	~minutes	Auto-refreshed on every request failure
Session ID	Per MCP session	Auto-extracted on MCP start

v0.1.9+: The server now automatically handles token expiration:

1. Refreshes CSRF tokens immediately when expired
2. Reloads cookies from disk if updated externally
3. Runs headless browser auth if profile has saved login

You can also call refresh_auth() to explicitly reload tokens.

If automatic refresh fails (Google login fully expired), run nlm login again.

Troubleshooting

uv tool upgrade Not Installing Latest Version

Symptoms:

• Running uv tool upgrade notebooklm-mcp-cli installs an older version (e.g., 0.1.5 instead of 0.1.9)
• uv cache clean doesn't fix the issue

Why this happens: uv tool upgrade respects version constraints from your original installation. If you initially installed an older version or with a constraint, upgrade stays within those bounds by design.

Fix — Force reinstall:

uv tool install --force notebooklm-mcp-cli

This bypasses any cached constraints and installs the absolute latest version from PyPI.

Verify:

uv tool list | grep notebooklm
# Should show: notebooklm-mcp-cli v0.1.9 (or latest)

Limitations

• Rate limits: Free tier has ~50 queries/day
• No official support: API may change without notice
• Cookie expiration: Need to re-extract cookies every few weeks

Contributing

See CLAUDE.md for detailed API documentation and how to add new features.

Vibe Coding Alert

Full transparency: this project was built by a non-developer using AI coding assistants. If you're an experienced Python developer, you might look at this codebase and wince. That's okay.

The goal here was to scratch an itch - programmatic access to NotebookLM - and learn along the way. The code works, but it's likely missing patterns, optimizations, or elegance that only years of experience can provide.

This is where you come in. If you see something that makes you cringe, please consider contributing rather than just closing the tab. This is open source specifically because human expertise is irreplaceable. Whether it's refactoring, better error handling, type hints, or architectural guidance - PRs and issues are welcome.

Think of it as a chance to mentor an AI-assisted developer through code review. We all benefit when experienced developers share their knowledge.

Credits

Special thanks to:

• Le Anh Tuan (@latuannetnam) for contributing the HTTP transport, debug logging system, and performance optimizations.
• David Szabo-Pele (@davidszp) for the source_get_content tool and Linux auth fixes.
• saitrogen (@saitrogen) for the research polling query fallback fix.
• devnull03 (@devnull03) for multi-browser CDP authentication support (Arc, Brave, Edge, Chromium, Vivaldi, Opera).
• VooDisss (@VooDisss) for multi-browser authentication improvements.
• codepiano (@codepiano) for the configurable DevTools timeout for the auth CLI.
• Tony Hansmann (@997unix) for contributing the nlm setup and nlm doctor commands and CLI Guide documentation.
• Fabiana Furtado (@fabianafurtadoff) for batch operations, cross-notebook query, pipelines, and smart select/tagging (PR #90).
• Amy-Ra-lph (@Amy-Ra-lph) for security hardening: TOCTOU-safe credential storage, sensitive cookie redaction from debug logs, and pinning all CI actions to full commit SHAs (PRs #205–207).
• Kyle Brodeur (@kylebrodeur) for WSL2 authentication support with Windows Chrome integration (PR #138).
• Robiton (@Robiton) for enterprise NotebookLM support via configurable base URL (PR #114).
• pjeby (@pjeby) for connection pooling and fast startup improvements (PR #54).
• beausea (@beausea) for making the interface language configurable via the NOTEBOOKLM_HL environment variable (PR #59).
• JumpLao (@JumpLao) for extended audio, video, and image format support (PR #82).
• cbruyndoncx (@cbruyndoncx) for including cited_text passages in query output (PR #81).
• zxyasfas (@zxyasfas) for cited-only research import (PR #188).
• Serdar Akın (@SERDAR-AKIN) for the multi-probe AuthHealthChecker that fixes false "stale" reports for semi-stale cookies (PR #219).

Star History

License

MIT License