notebooklm-mcp-cli

# NotebookLM MCP CLI > Skill by [ara.so](https://ara.so) — Devtools Skills collection. ## Overview NotebookLM MCP CLI provides programmatic access to Google NotebookLM through: - **CLI (`nlm`)**: Direct terminal commands for scripting and automation - **MCP Server (`notebooklm-mcp`)**: Model Context Protocol server for AI agents (Claude, Gemini, Cursor, etc.) Both interfaces access the same NotebookLM API capabilities: notebook management, source addition, audio/video generation, research automation, and sharing. **Important**: Uses undocumented internal APIs requiring browser cookie extraction. Supports NotebookLM Pro/free and Google AI Ultra accounts. ## Installation ```bash # Recommended: Install with uv uv tool install notebooklm-mcp-cli # Alternative: pip pip install notebooklm-mcp-cli # Alternative: pipx pipx install notebooklm-mcp-cli # Verify installation nlm --version ``` This installs both: - `nlm` - CLI interface - `notebooklm-mcp` - MCP server ## Authentication ### Initial Setup ```bash # Auto mode: launches browser for cookie extraction nlm login # Check authentication status nlm login --check # Manual mode with cookie file nlm login --manual --file cookies.txt ``` ### Profile Management (Multiple Google Accounts) ```bash # Create named profiles nlm login --profile work nlm login --profile personal # Switch profiles nlm login switch work # List all profiles nlm login profile list # Delete a profile nlm login profile delete personal ``` ### Browser Selection ```bash # Set preferred browser nlm config set auth.browser brave # Supported: chrome, arc, brave, edge, chromium, firefox ``` ## CLI Usage ### Notebook Management ```python # List all notebooks nlm notebook list # Create a new notebook nlm notebook create "Research Project" # Get notebook details nlm notebook get <notebook-id> # Delete a notebook nlm notebook delete <notebook-id> # Rename a notebook nlm notebook rename <notebook-id> "New Name" ``` ### Adding Sources ```python # Add URL source nlm source add <notebook-id> --url "https://example.com" # Add text source nlm source add <notebook-id> --text "Your content here" --title "Notes" # Add Google Drive file nlm source add <notebook-id> --drive-id "1ABC..." --title "Document" # Add local file (uploads to Drive first) nlm source add <notebook-id> --file ./document.pdf # Add multiple sources at once nlm source add <notebook-id> \ --url "https://site1.com" \ --url "https://site2.com" \ --text "Summary notes" # List sources in notebook nlm source list <notebook-id> # Delete a source nlm source delete <notebook-id> <source-id> ``` ### Querying Notebooks ```python # Ask a question (persists to web UI) nlm notebook query <notebook-id> "What are the key findings?" # Query with custom settings nlm notebook query <notebook-id> "Summarize this" \ --grounding "Always cite sources" \ --format-as markdown ``` ### Studio Content Creation ```python # Create audio podcast (Deep Dive) nlm studio create <notebook-id> --type audio --confirm # Create video presentation nlm studio create <notebook-id> --type video --confirm # Create slides nlm studio create <notebook-id> --type slides --confirm # Interactive mode (prompts for confirmation) nlm studio create <notebook-id> --type audio # List studio artifacts nlm studio list <notebook-id> ``` ### Revising Slides ```python # Revise specific slides with instructions nlm slides revise <notebook-id> <artifact-id> \ --slides 1,3,5 \ --instruction "Add more technical details and code examples" # Revise all slides nlm slides revise <notebook-id> <artifact-id> \ --instruction "Make the tone more casual" # Check revision status nlm slides status <notebook-id> <revision-id> ``` ### Downloading Artifacts ```python # Download audio file nlm download audio <notebook-id> <artifact-id> --output podcast.wav # Download video nlm download video <notebook-id> <artifact-id> --output presentation.mp4 # Download slides as PDF nlm download slides <notebook-id> <artifact-id> --output deck.pdf # Auto-generate filename nlm download audio <notebook-id> <artifact-id> ``` ### Sharing ```python # Enable public link nlm share public <notebook-id> # Invite specific email nlm share invite <notebook-id> user@example.com # Get share status nlm share status <notebook-id> # Revoke public link nlm share revoke <notebook-id> ``` ### Research Automation ```python # Start web research with queries nlm research start <notebook-id> \ --query "quantum computing breakthroughs 2024" \ --query "quantum error correction" # Drive-based research nlm research drive <notebook-id> \ --drive-id "1ABC..." \ --query "financial trends" # Check research status nlm research status <notebook-id> <research-id> ``` ### Batch Operations ```python # Batch query across notebooks nlm batch query "What are the main themes?" \ --notebooks <id1> <id2> <id3> # Batch create notebooks nlm batch create \ --names "Project A" "Project B" "Project C" # Batch delete nlm batch delete --notebooks <id1> <id2> <id3> --confirm ``` ### Cross-Notebook Queries ```python # Query across multiple notebooks nlm cross query "Compare the methodologies" \ --notebooks <id1> <id2> <id3> # Smart notebook selection by tags nlm cross query "What are common themes?" \ --tags research papers ``` ### Tagging ```python # Add tags to notebook nlm tag add <notebook-id> research important # List all tags nlm tag list # Select notebooks by tag nlm tag select research ``` ### Pipelines (Multi-Step Workflows) ```python # Run a predefined pipeline nlm pipeline run research-to-podcast \ --notebook <notebook-id> \ --urls "https://site1.com,https://site2.com" # List available pipelines nlm pipeline list # Create custom pipeline (YAML) cat > my-pipeline.yaml <<EOF name: research-to-podcast steps: - type: source_add urls: {{ urls }} - type: studio_create content_type: audio EOF nlm pipeline run my-pipeline.yaml --notebook <id> --urls "https://..." ``` ## MCP Server Setup ### Automatic Configuration ```bash # Add to AI tools automatically 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 nlm setup add cline nlm setup add antigravity # Generate JSON config for custom tools nlm setup add json # List configured tools nlm setup list # Remove from a tool nlm setup remove claude-code ``` ### Manual MCP Configuration If automatic setup doesn't work, manually add to your MCP client config: ```json { "mcpServers": { "notebooklm-mcp": { "command": "notebooklm-mcp", "args": [], "env": { "NOTEBOOKLM_PROFILE": "default" } } } } ``` **Config file locations:** - **Claude Desktop**: `~/Library/Application Support/Claude/claude_desktop_config.json` (macOS) - **Cursor**: `~/Library/Application Support/Cursor/User/globalStorage/rooveterinaryinc.roo-cline/settings/cline_mcp_settings.json` - **Gemini CLI**: `~/.config/gemini-ai/mcp.json` ### Install AI Skills (Optional) ```bash # Install expert guide for your AI assistant nlm skill install cline nlm skill install claude-code nlm skill install gemini # Update skills nlm skill update cline # List installed skills nlm skill list ``` ## MCP Tools Reference ### Core Tools ```python # List notebooks notebook_list() # Create notebook notebook_create(title="Research Project") # Add sources source_add( notebook_id="abc123", urls=["https://example.com"], texts=[{"content": "Notes", "title": "Summary"}], drive_ids=["1ABC..."], files=["/path/to/file.pdf"] ) # Query notebook notebook_query( notebook_id="abc123", query="What are the key findings?", grounding_instruction="Cite sources", format_as="markdown" ) # Create studio content studio_create( notebook_id="abc123", content_type="audio", # or "video", "slides" confirm=True ) # Download artifact download_artifact( notebook_id="abc123", artifact_id="xyz789", artifact_type="audio", # or "video", "slides" output_path="podcast.wav" ) # Share notebook notebook_share_public(notebook_id="abc123") notebook_share_invite(notebook_id="abc123", email="user@example.com") ``` ### Advanced Tools ```python # Research automation research_start( notebook_id="abc123", queries=["topic 1", "topic 2"], source_type="web" # or "drive" ) # Batch operations batch_query( query="Compare approaches", notebook_ids=["id1", "id2", "id3"] ) # Cross-notebook query cross_notebook_query( query="What are common patterns?", notebook_ids=["id1", "id2"], tags=["research"] ) # Pipeline execution pipeline_run( pipeline_name="research-to-podcast", notebook_id="abc123", params={"urls": ["https://site.com"]} ) # Slide revision studio_revise( notebook_id="abc123", artifact_id="xyz789", instruction="Add more technical details", slide_numbers=[1, 3, 5] ) ``` ## Common Workflows ### Research Paper to Podcast ```bash #!/bin/bash # Create notebook NOTEBOOK_ID=$(nlm notebook create "Research Summary" | jq -r '.id') # Add sources nlm source add $NOTEBOOK_ID \ --url "https://arxiv.org/pdf/2024.12345.pdf" \ --url "https://related-paper.com" # Generate podcast nlm studio create $NOTEBOOK_ID --type audio --confirm # Download when ready (check status first) sleep 60 # Wait for generation ARTIFACT_ID=$(nlm studio list $NOTEBOOK_ID | jq -r '.[0].id') nlm download audio $NOTEBOOK_ID $ARTIFACT_ID --output research.wav ``` ### Automated Weekly Research Digest ```python #!/usr/bin/env python3 import subprocess import json # Create notebook result = subprocess.run( ["nlm", "notebook", "create", "Weekly Digest"], capture_output=True, text=True ) notebook_id = json.loads(result.stdout)["id"] # Add URLs from research tracking urls = [ "https://news.ycombinator.com/best", "https://paperswithcode.com/latest", ] subprocess.run([ "nlm", "source", "add", notebook_id, *[f"--url={url}" for url in urls] ]) # Query for summary subprocess.run([ "nlm", "notebook", "query", notebook_id, "Summarize the key developments this week" ]) # Generate video presentation subprocess.run([ "nlm", "studio", "create", notebook_id, "--type=video", "--confirm" ]) ``` ### Multi-Notebook Cross-Analysis ```bash # Tag related notebooks nlm tag add nb1 quarterly-review finance nlm tag add nb2 quarterly-review finance nlm tag add nb3 quarterly-review finance # Query across all tagged notebooks nlm cross query "Compare revenue growth patterns" --tags quarterly-review finance # Or specify exact notebooks nlm cross query "What are the common risks?" --notebooks nb1 nb2 nb3 ``` ## Configuration ```bash # View all settings nlm config list # Set auth browser preference nlm config set auth.browser brave # Set default output directory nlm config set download.output_dir ~/Downloads/notebooklm # Enable debug logging nlm config set logging.level debug # Reset to defaults nlm config reset ``` ## Troubleshooting ### Diagnose Issues ```bash # Run comprehensive diagnostics nlm doctor # Check specific components nlm login --check nlm setup list ``` ### Common Issues **Authentication expired:** ```bash nlm login --force # Re-authenticate ```