NotebookLM

NotebookLM = external RAG engine that offloads reading from your context window. Uses the notebooklm-mcp-cli MCP server (PyPI, v0.4.8+) to create notebooks, manage sources, generate content, and query with grounded AI responses. Supports batch operations across notebooks, pipelines, and multilingual content generation.

Disclaimer: Uses internal undocumented Google APIs via browser authentication. Sessions last ~20 minutes. API may change without notice.

Prerequisites

1. Install: uv tool install notebooklm-mcp-cli (or pip install notebooklm-mcp-cli)
2. Authenticate: nlm login (opens browser, session ~20 min)
3. Configure MCP: nlm setup add claude-code (auto-configures .mcp.json) or nlm setup add all for multi-tool setup
4. Verify: nlm login --check to confirm active session
5. Upgrade: uv tool upgrade notebooklm-mcp-cli — restart MCP server after upgrade

Decision Tree — Which Rule to Read

What are you trying to do?
│
├── Create / manage notebooks
│   ├── List / get / rename ──────► notebook_list, notebook_get, notebook_rename
│   ├── Create new notebook ──────► notebook_create
│   └── Delete notebook ──────────► notebook_delete (irreversible!)
│
├── Add sources to a notebook
│   ├── URL / YouTube ────────────► source_add(type=url)
│   ├── Plain text ───────────────► source_add(type=text)
│   ├── Local file ───────────────► source_add(type=file)
│   ├── Google Drive ─────────────► source_add(type=drive)
│   ├── Rename a source ──────────► source_rename
│   └── Manage sources ──────────► rules/setup-quickstart.md
│
├── Query a notebook (AI chat)
│   ├── Ask questions ────────────► notebook_query
│   └── Configure chat style ────► chat_configure
│
├── Generate studio content
│   ├── 9 artifact types ────────► rules/workflow-studio-content.md
│   ├── Revise slides ───────────► studio_revise (creates new deck)
│   └── Export to Docs/Sheets ──► export_artifact
│
├── Research & discovery
│   └── Web/Drive research ──────► rules/workflow-research-discovery.md
│
├── Notes (capture insights)
│   └── Create/list/update/delete ► note (unified tool)
│
├── Sharing & collaboration
│   └── Public links / invites / batch ► rules/workflow-sharing-collaboration.md
│
├── Batch & cross-notebook
│   ├── Query across notebooks ────► cross_notebook_query
│   ├── Bulk operations ───────────► batch (query, add-source, create, studio)
│   └── Multi-step pipelines ──────► rules/workflow-batch-pipelines.md
│
├── Organization
│   └── Tag notebooks ─────────────► tags
│
└── Workflow patterns
    ├── Second brain ─────────────► rules/workflow-second-brain.md
    ├── Research offload ─────────► rules/workflow-research-offload.md
    └── Knowledge base ──────────► rules/workflow-knowledge-base.md

Quick Reference

Category	Rule	Impact	Key Pattern
Setup	setup-quickstart.md	HIGH	Auth, MCP config, source management, session refresh
Workflows	workflow-second-brain.md	HIGH	Decision docs, project hub, agent interop
Workflows	workflow-research-offload.md	HIGH	Synthesis, onboarding, token savings
Workflows	workflow-knowledge-base.md	HIGH	Debugging KB, security handbook, team knowledge
Workflows	workflow-studio-content.md	MEDIUM	9 artifact types (audio overview, deep dive, slides...)
Research	workflow-research-discovery.md	HIGH	Web/Drive research async flow
Collaboration	workflow-sharing-collaboration.md	MEDIUM	Public links, collaborator invites, batch sharing
Batch	workflow-batch-pipelines.md	HIGH	Cross-notebook queries, batch ops, pipelines
Release	workflow-versioned-notebooks.md	HIGH	Per-release notebooks with changelog + diffs

Total: 9 rules across 5 categories

MCP Tools by API Group

Group	Tools	Count
Notebooks	notebook_list, notebook_create, notebook_get, notebook_describe, notebook_rename, notebook_delete	6
Sources	source_add, source_rename, source_list_drive, source_sync_drive, source_delete, source_describe, source_get_content	7
Querying	notebook_query, chat_configure	2
Studio	studio_create, studio_status, studio_list_types, studio_revise, studio_delete	5
Research	research_start, research_status, research_import	3
Sharing	notebook_share_status, notebook_share_public, notebook_share_invite, notebook_share_batch	4
Notes	note (unified: list/create/update/delete)	1 (4 actions)
Downloads	download_artifact	1
Export	export_artifact (Google Docs/Sheets)	1
Batch	batch (multi-notebook ops), cross_notebook_query	2
Pipelines	pipelines (ingest-and-podcast, research-and-report, multi-format)	1
Tags	tags (organize and smart-select notebooks)	1
Auth	save_auth_tokens, refresh_auth, server_info	3

Total: 37 tools across 13 groups (v0.4.8+)

Key Decisions

Decision	Recommendation
New notebook vs existing	One notebook per project/topic; add sources to existing
Source type	URL for web, text for inline, file for local docs, drive for Google Docs
Large sources	Split >50K chars into multiple sources for better retrieval
Auth expired?	nlm login --check; sessions last ~20 min, re-auth with nlm login
Studio content	Use studio_create, poll with studio_status (generation takes 2-5 min)
Research discovery	research_start for web/Drive discovery, then research_import to add findings
Release notebooks	One notebook per minor version; upload CHANGELOG + key skill diffs as sources
Query vs search	notebook_query for AI-grounded answers; source_get_content for raw text
Notes vs sources	Notes for your insights/annotations; sources for external documents
Infographic style	11 visual styles via infographic_style param on studio_create
Slide revision	Use studio_revise to edit individual slides (creates a new deck)
Export artifacts	export_artifact sends reports → Google Docs, data tables → Sheets
Language	language param on studio_create accepts BCP-47 codes (e.g., he for Hebrew, en, es, ja)
Batch operations	Use batch for multi-notebook ops; cross_notebook_query for aggregated answers
Pipelines	ingest-and-podcast / research-and-report / multi-format for multi-step workflows

Example

# 1. Create a notebook for your project
notebook_create(title="Auth Refactor Research")

# 2. Add sources (docs, articles, existing code analysis)
source_add(notebook_id="...", type="url", url="https://oauth.net/2.1/")
source_add(notebook_id="...", type="text", content="Our current auth uses...")
source_add(notebook_id="...", type="file", path="/docs/auth-design.md")

# 3. Query with grounded AI responses
notebook_query(notebook_id="...", query="What are the key differences between OAuth 2.0 and 2.1?")

# 4. Generate a deep dive audio overview (supports language param)
studio_create(notebook_id="...", artifact_type="audio", audio_format="deep_dive", language="he", confirm=True)
studio_status(notebook_id="...")  # Poll until complete

# 5. Capture insights as notes
note(notebook_id="...", action="create", content="Key takeaway: PKCE is mandatory in 2.1")

Common Mistakes

• Forgetting auth expiry — Sessions last ~20 min. Always check with nlm login --check before long workflows. Re-auth with nlm login.
• One giant notebook — Split by project/topic. One notebook with 50 sources degrades retrieval quality.
• Huge single sources — Split documents >50K characters into logical sections for better chunking and retrieval.
• Not polling studio_status — Studio content generation takes 2-5 minutes. Poll studio_status instead of assuming instant results.
• Ignoring source types — Use type=url for web pages (auto-extracts), type=file for local files. Using type=text for a URL gives you the URL string, not the page content.
• Deleting notebooks without checking — notebook_delete is irreversible. List contents with source_list_drive and note(action=list) first.
• Skipping research_import — research_start discovers content but does not add it. Use research_import to actually add findings as sources.
• Raw queries on empty notebooks — notebook_query returns poor results with no sources. Add sources before querying.
• Ignoring language param — studio_create supports BCP-47 language codes (e.g., he, ar, ja). Defaults to English if omitted.
• Batch without purpose — batch and cross_notebook_query are powerful but add latency. Use for multi-project synthesis, not single-notebook tasks.

Related Skills

• ork:mcp-patterns — MCP server building, security, and composition patterns
• ork:web-research-workflow — Web research strategies and source evaluation
• ork:memory — Memory fabric for cross-session knowledge persistence
• ork:security-patterns — Input sanitization and layered security