NotebookLM Research Agent

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name: notebooklm-research description: > Full-autopilot AI research agent powered by Google NotebookLM (notebooklm-py v0.3.4). Ingests sources (URL, text, PDF, DOCX, YouTube, Google Drive), runs deep web research, asks cited questions, and generates 10 native artifact types (audio podcast, video, cinematic video, slide deck, report, quiz, flashcards, mind map, infographic, data table, study guide). Produces original content drafts via Claude, with optional publishing to social platforms via threads-viral-agent integration. Use this skill when the user mentions: NotebookLM, research with sources, create notebook, generate podcast from articles, turn research into content, trending topic research, research pipeline, source-based analysis, cited research answers, generate slides, generate quiz, make flashcards, deep web research, create infographic, compare sources, research report, study guide, source analysis, or knowledge synthesis.

NotebookLM Research Agent

A fully autonomous AI research agent that ingests sources into Google NotebookLM, runs deep web research, synthesizes knowledge through cited Q&A and 9 downloadable artifact types, creates polished content drafts, and optionally publishes to social platforms.

**Zero-cost research engine** -- NotebookLM is free. No API keys. No per-query charges.

Authentication

NotebookLM uses RPC/HTTP calls after a one-time browser cookie auth. No browser automation per operation -- the session is stored and reused.

~/.notebooklm/storage_state.json

Login once via the built-in CLI:

notebooklm login              # One-time browser auth, saves session
notebooklm login --check      # Verify stored session is still valid

The session persists until Google expires it (typically weeks). All scripts and the MCP server auto-load the stored session. No API keys or environment variables needed.

Architecture Overview

**Core Principle: NotebookLM provides cited research, Claude creates content.**

NotebookLM handles source ingestion, indexing, deep web research, cited answers, and native artifact generation (9 downloadable types). Claude uses that research output to write original articles, social posts, and reports. The pipeline is zero-cost and produces citation-backed content.

Component	Role
notebooklm-py (v0.3.4)	Python client for NotebookLM (8 sub-APIs, 50+ methods, built-in CLI)
notebooklm CLI	Built-in CLI: notebooklm login, notebook, source, chat, generate, download, research, share
MCP Server (mcp_server/)	FastMCP server exposing 13 tools for Claude Code / Cursor / Gemini CLI
Wrapper CLI (scripts/)	Our higher-level wrappers: notebooklm_client.py, pipeline.py
LLM (Claude)	Content creator (writes original text using NotebookLM research)
trend-pulse (optional)	Trending topic discovery for research-to-content pipelines
threads-viral-agent (optional)