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Notebooklm MCP

by roomi-fields

Automates NotebookLM through MCP and a 54-endpoint REST API for grounded Q&A, source workflows, batch research, and Studio artifacts.

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Install Notebooklm MCP

Pick your client, then add it in one click or paste the config.

STDIONode.js
~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "roomi-fields-notebooklm-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "@roomi-fields/notebooklm-mcp"
      ],
      "env": {
        "NOTEBOOKLM_API_KEY": "YOUR_VALUE_HERE"
      }
    }
  }
}

Settings → Developer → Edit Config, merge this into mcpServers, then fully quit and reopen Claude Desktop.

Values are written into the snippet above so you can paste it as is. They never leave your browser.

Install not yet sandbox-tested— we haven't run this command through our automated sandbox yet. Not a red flag; we're working through the catalog.

Overview

roomi-fields/notebooklm-mcp connects AI agents and HTTP workflows to Google NotebookLM, also known as Gemini Notebook, through MCP and a 54-endpoint REST API. It supports citation-backed questions, notebook and source management, multi-turn sessions, batch processing, and generation of audio, video, infographics, reports, presentations, data tables, flashcards, quizzes, and mind maps. The implementation uses NotebookLM’s internal RPC interface with a Playwright browser fallback, and can rotate multiple Google accounts with automatic reauthentication. Reach for it when an agent, automation platform, or scheduled job needs grounded NotebookLM answers or downloadable Studio output.

Use cases

  • Ask citation-backed questions across uploaded research sources
  • Build n8n, Zapier, or Make workflows around NotebookLM
  • Batch literature-review questions across notebooks and accounts
  • Generate podcasts, videos, reports, and presentations from one source set
  • Cache cited answers as structured JSON for later indexing

Key features

  • MCP and 54-endpoint HTTP REST interfaces
  • Citation extraction with five output formats
  • Notebook and source management
  • Multi-account rotation with automatic reauthentication
  • Studio artifact generation and downloads
  • Resumable batch answers written as structured JSON

Security & health

What it can reach and how reliably it runs — from our own checks, not the maintainer’s claims.

ActiveLast checked Today

Recent health check succeeded.

19/20 checks healthy over the last 84d

Supply-chain signal

1 high-severity advisory on record for this package. Most advisories affect transitive dependencies and may not be exploitable in this server's actual usage — this is a directional signal, not a security audit.

Critical 0High 1Medium 0Low 0

Scanned 14d ago via OSV.dev · @roomi-fields/notebooklm-mcp (npm)

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars218Stargazers on the source repository.
npm downloads3kPackage downloads in the last 30 days.
Last commit3d agoMost recent push to the default branch.
Directory activity9 viewsConfig copies, upvotes, and views on AllMCPs.

How Notebooklm MCP works

What roomi-fields/notebooklm-mcp does

roomi-fields/notebooklm-mcp exposes Google NotebookLM through two interfaces: an MCP server for agent clients and a 54-endpoint HTTP REST API for tools such as n8n, Zapier, Make, and curl. NotebookLM is also referred to as Gemini Notebook; the project continues to use its original package and repository name.

The service can create and manage notebooks, add sources, ask questions, maintain conversational sessions, and return answers with citations. Citation output can include source names and quoted excerpts, with formats covering no citations, inline citations, footnotes, JSON, and expanded results. It also provides programmatic access to Studio generation, including audio overviews, videos, infographics, reports, presentations, data tables, flashcards, quizzes, and mind maps.

How it works

The implementation first uses NotebookLM’s internal batchexecute RPC interface. A Playwright browser path serves as an automatic fallback when the RPC route cannot be used. These are the same undocumented service interfaces used by the NotebookLM web application rather than an official Google API.

MCP clients can delegate research and content tasks to the server, while ordinary HTTP clients can call the REST API without an agent runtime or MCP client. Multi-account rotation and automatic reauthentication support longer-running workloads. The vault_batch workflow writes answers and citations to disk as structured JSON, allowing results to be inspected, searched, compared, or indexed later. Batch processing can resume after an interruption.

Setup and configuration

Node.js 22 or newer is required. The project can run as an MCP service for clients such as Claude Code, Cursor, and Codex, or as an HTTP service for workflow automation and application backends.

HTTP deployments that need remote access or Docker use require NOTEBOOKLM_API_KEY. The HTTP API binds to loopback by default, rejects origins that are not listed, and expects a bearer token when protected access is enabled. A dedicated Google account is recommended for automation, particularly for scheduled or high-volume jobs.

Tools and capabilities

  • Ask NotebookLM questions grounded in notebook sources.
  • Return citations in several output formats, including quoted source excerpts.
  • Create notebooks, add sources, and manage notebook content.
  • Maintain multi-turn sessions with reauthentication when sessions expire.
  • Generate and download audio overviews, videos, infographics, reports, presentations, and data tables.
  • Generate flashcards, quizzes, and mind maps from notebook material.
  • Run large question batches across notebooks and accounts, then persist structured answers to disk.
  • Expose the same underlying functionality through MCP and HTTP REST.

Limitations and notes

This is an unofficial integration and is not affiliated with Google. Its RPC and browser interfaces are undocumented and may change when NotebookLM changes; the project maintains both paths to handle such changes.

NotebookLM’s own quotas still apply, so high-volume work can be constrained by account limits. Account rotation helps distribute batch workloads but does not remove those service quotas. The HTTP API’s security controls are especially relevant when running outside a local development environment: remote access and Docker deployments require an API key, and the service should not be treated as an unauthenticated network endpoint.

Read the full README View source on GitHub

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Frequently Asked Questions about Notebooklm MCP

roomi-fields/notebooklm-mcp is an MCP server that connects AI agents to Google NotebookLM, also known as Gemini Notebook. Its main tools support citation-backed questions, notebook and source management, session handling, batch research, and Studio generation for audio, video, reports, presentations, infographics, and other artifacts.

Install it in a Node.js 22-or-newer environment and configure it as an MCP service for a compatible client. It can also run as an HTTP REST service for n8n, Zapier, Make, curl, or application backends.

Yes, roomi-fields/notebooklm-mcp is intended to work with Cursor through MCP. The project also identifies Claude Code and Codex as supported MCP clients.

Set `NOTEBOOKLM_API_KEY` when using remote access or Docker deployments. The HTTP service binds to loopback, rejects unlisted origins, and uses a bearer token for protected access.

Yes, it can generate and download audio overviews and videos from notebook sources. Video generation supports brief and explainer formats, while audio supports custom instructions and more than 80 languages.

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