sergeyramas/notebooklm-claude-memory

A compact landing-page project that shows how to use Google NotebookLM together with the open-source Claude Code "skill" to give AI agents a free, large-capacity research memory. Intended for developers and hobbyists building personal agents or research assistants who want a low-cost, high-context memory without vector DBs or extra compute. Key features: - Single-file static site (index.html): no build or dependencies, easy local preview and instant Vercel deploy. - Leverages NotebookLM (free: ~1M-token context, 300 docs, supports video/PDF/audio) to store the research base. - Claude Code skill sidesteps NotebookLM access limits and compute-only constraints, keeping Claude token usage low. - No Pinecone/Supabase required; simple setup (git clone + Google login) in ~10 minutes. - Links to the MIT-licensed skill repo, NotebookLM, and source video; deployment instructions included.

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