MCP Guide

Complete reference for the NotebookLM MCP server — 35 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

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_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)
• 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, max_wait=300)  # wait for completion
3. 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)  # poll until complete
6. download_artifact(notebook_id, artifact_type="audio", output_path="podcast.mp3")

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)

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

MCP Server Options

Environment Variables

Context Window Tips

This MCP has 35 tools which consume context. Best practices:

• Disable when not using: In Claude Code, use @notebooklm-mcp to toggle
• Use unified tools: source_add, studio_create, download_artifact handle multiple operations each
• Poll wisely: Use studio_status sparingly - artifacts take 1-5 minutes

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