notebooklm-mcp-cli

MCP Guide

Complete reference for the NotebookLM MCP server — 39 tools for AI assistants.

Installation

# Install the package
uv tool install notebooklm-mcp-cli

# Add to Claude Code
claude mcp add --scope user notebooklm-mcp notebooklm-mcp

# Add to Gemini CLI
gemini mcp add --scope user notebooklm-mcp notebooklm-mcp

Server naming: Use notebooklm-mcp (the default) as the server name when registering with your agent. If you have a legacy browser-automation NotebookLM MCP installed under a different name (e.g. notebooklm), remove that one first — agents like Hermes get confused when two servers expose overlapping tool names (notebook_create, source_add, notebook_query, …).

See the Migrating from another NotebookLM MCP section in the Getting Started guide for the full step-by-step.

Authentication

Before using MCP tools, authenticate:

nlm login

Or use the standalone auth tool:

nlm login

Tool Reference

Notebooks (6 tools)

Sources (6 tools)

source_list_drive parameters:

source_list_drive(
    notebook_id="...",
    skip_freshness=False,  # True skips per-source freshness API calls for faster listing
)

source_add parameters:

source_add(
    notebook_id="...",
    source_type="url",        # url | text | file | drive
    url="https://...",        # for source_type=url
    text="...",               # for source_type=text
    title="...",              # optional title
    file_path="/path/to.pdf", # for source_type=file
    document_id="...",        # for source_type=drive
    doc_type="doc",           # doc | slides | sheets | pdf
    wait=True,                # wait for processing to complete
    wait_timeout=120.0        # seconds to wait
)

Querying (2 tools)

Studio Content (4 tools)

studio_create artifact types:

• audio - Podcast (formats: deep_dive, brief, critique, debate)
• video - Video overview (formats: explainer, brief, cinematic, short)
• report - Text report (Briefing Doc, Study Guide, Blog Post)
• quiz - Multiple choice quiz
• flashcards - Study flashcards
• mind_map - Visual mind map
• slide_deck - Presentation slides
• infographic - Visual infographic
• data_table - Structured data table

Downloads (1 tool)

download_artifact types: audio, video, report, mind_map, slide_deck, infographic, data_table, quiz, flashcards

Exports (1 tool)

Research (3 tools)

Notes (1 unified tool)

note actions:

note(notebook_id, action="list")             # List all notes
note(notebook_id, action="create", content="...", title="...")
note(notebook_id, action="update", note_id="...", content="...")
note(notebook_id, action="delete", note_id="...", confirm=True)

Sharing (3 tools)

Auth (2 tools)

Server (1 tool)

Batch & Cross-Notebook (2 tools)

batch actions:

batch(action="query", query="What are the key findings?", notebook_names="AI Research, Dev Tools")
batch(action="add_source", source_url="https://...", tags="ai,research")
batch(action="create", titles="Project A, Project B, Project C")
batch(action="delete", notebook_names="Old Project", confirm=True)
batch(action="studio", artifact_type="audio", tags="research", confirm=True)

cross_notebook_query:

cross_notebook_query(query="Compare approaches", notebook_names="Notebook A, Notebook B")
cross_notebook_query(query="Summarize", tags="ai,research")
cross_notebook_query(query="Everything", all=True)

Pipelines (1 tool)

pipeline actions:

pipeline(action="list")  # List available pipelines
pipeline(action="run", notebook_id="...", pipeline_name="ingest-and-podcast", input_url="https://...")

Built-in pipelines: ingest-and-podcast, research-and-report, multi-format

Tags & Smart Select (1 tool)

tag actions:

tag(action="add", notebook_id="...", tags="ai,research,llm")
tag(action="remove", notebook_id="...", tags="ai")
tag(action="list")  # List all tagged notebooks
tag(action="select", query="ai research")  # Find notebooks by tag match

Example Workflows

Research → Podcast

1. research_start(query="AI trends 2026", mode="deep")
2. research_status(notebook_id, auto_import=True)  # waits up to 15 min, imports automatically
# Or review sources first, then import manually:
2a. research_status(notebook_id)  # waits up to 15 min, returns next_action hint
2b. research_import(notebook_id, task_id, cited_only=True, timeout=600)  # optional cited subset
4. studio_create(notebook_id, artifact_type="audio", confirm=True)
5. studio_status(notebook_id, artifact_id=created_artifact_id)  # poll one artifact
6. download_artifact(notebook_id, artifact_type="audio", output_path="podcast.mp3")

studio_status returns lean fields and at most 20 artifacts by default. Poll a new artifact with artifact_id, page large notebooks with limit/offset, and set include_details=True only when prompts, source IDs, report content, or media details are required.

Add Sources with Wait

source_add(notebook_id, source_type="url", url="https://...", wait=True)
# Returns when source is fully processed and ready for queries

Generate Study Materials

studio_create(notebook_id, artifact_type="quiz", question_count=10, confirm=True)
studio_create(notebook_id, artifact_type="flashcards", difficulty="hard", confirm=True)
studio_create(notebook_id, artifact_type="report", report_format="Study Guide", confirm=True)
studio_create(notebook_id, artifact_type="audio", language="es-419", confirm=True)

For Audio Overviews, NotebookLM has been observed using BCP-47 region subtags to select the voice accent. es and es-ES produce Spain Spanish, while es-US and es-419 produce Latin-American Spanish. The generation prompt does not reliably override the accent. Treat this as observed behavior, not a guaranteed API contract.

Tag, Batch & Cross-Notebook

# Tag notebooks for organization
tag(action="add", notebook_id="abc", tags="ai,research")
tag(action="add", notebook_id="def", tags="ai,product")

# Find relevant notebooks
tag(action="select", query="ai research") 

# Query across tagged notebooks
cross_notebook_query(query="What are the main conclusions?", tags="ai")

# Batch generate podcasts for all tagged notebooks
batch(action="studio", artifact_type="audio", tags="ai", confirm=True)

Pipeline Automation

# List available pipelines
pipeline(action="list")

# Run a full ingest-and-podcast workflow
pipeline(action="run", notebook_id="abc", pipeline_name="ingest-and-podcast", input_url="https://example.com")

Configuration

Planning to connect from Claude web/mobile or expose the server over a network? Read Remote MCP Deployment first. HTTP transport support does not provide HTTPS, caller authentication, per-user NotebookLM accounts, or remote file transfer.

MCP Server Options

Environment Variables

Context Window Tips

This MCP has 39 tools which consume context. Best practices:

• Disable when not using: In Claude Code, use @notebooklm-mcp to toggle
• Hide tools you don't need: See Selective tool exposure below to expose only a subset
• Use unified tools: source_add, studio_create, download_artifact handle multiple operations each
• Poll wisely: Use studio_status sparingly - artifacts take 1-5 minutes

Selective tool exposure

Gating is opt-in: with no configuration all tools are visible. To reduce context, hide tools by group or by name via environment variables. Tools are hidden rather than removed, so no code changes are needed.

Resolution order (later wins): NOTEBOOKLM_DISABLED_GROUPS, then NOTEBOOKLM_DISABLED_TOOLS, then NOTEBOOKLM_ENABLED_TOOLS.

# Query-first setup: hide mutating groups, keep read + chat tools
export NOTEBOOKLM_DISABLED_GROUPS="notebooks_manage,sources_manage,studio,research,sharing,notes"

# Hide one extra tool, but keep studio_status from an otherwise-hidden group
export NOTEBOOKLM_DISABLED_TOOLS="tag"
export NOTEBOOKLM_ENABLED_TOOLS="studio_status"

Available groups: notebooks_read, notebooks_manage, sources_read, sources_manage, chat, query_multi, organization, automation, notes, auth, server, sharing, research, studio.

Unknown group names are ignored. Changes take effect on server restart.

IDE Configuration

The easiest way to configure any tool is with nlm setup:

nlm setup add claude-code       # Claude Code
nlm setup add gemini            # Gemini CLI
nlm setup add github-copilot    # GitHub Copilot
nlm setup add cursor            # Cursor
nlm setup add windsurf          # Windsurf
nlm setup add json              # Any other tool (interactive JSON generator)

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

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

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

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