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notebooklm-py
notebooklm-py is an unofficial Python API and CLI tool that provides programmatic access to Google Gemini Notebook features for research automation and AI agent workflows.
notebooklm-py serves as an unofficial Python API and CLI library for interacting with Google Gemini Notebook. It allows users to programmatically manage notebooks, ingest various source types like URLs, PDFs, YouTube videos, and Google Drive files, and extract insights or generated artifacts. The library enables AI agents—such as Claude Code and Codex—to utilize Gemini Notebook as a grounded memory layer and synthesis engine. Users can export generated content in formats like JSON, Markdown, CSV, and MP3, accessing batch features not available in the standard web interface. This tool is designed for developers and researchers who need to script automated research pipelines, generate multi-format media, or integrate grounded, cited knowledge bases into their own coding workflows.
notebooklm-py at a glance
- Best for: Researcher, Software engineer, Student
- Runs on: CLI, API, self-hosted
- Pricing: Free
- Released: January 2026
- Category: AI research tool
- Website: github.com/teng-lin/notebooklm-py
Key features
- Programmatic import of URLs, PDFs, YouTube, and Drive documents
- Automated generation of audio overviews, quizzes, and infographics
- Batch export of artifacts in JSON, Markdown, PDF, and CSV formats
- Integration with AI agents via MCP server, CLI, and Python API
- Scriptable research workflows for grounded, cited synthesis
- Persistent cross-session memory and notebook management
Use it for
- Building AI agents with grounded memory from custom document corpora
- Automating the creation of audio podcasts and study guides from text sources
- Extracting structured data like mind maps and tables from research notebooks
- Generating automated incident runbooks from technical documentation
Companions
Tools that articles about notebooklm-py recommend using with it, each with its job.
- Gemini Notebook — Built to work with Gemini Notebook.
- Perplexity — Cited web research to feed into your notebooks.
- Claude — Explains and builds on what your sources can't cover.
- Gemini — Gemini Deep Research reports become notebook sources.
- Quizlet — Turns NotebookLM output into spaced-repetition flashcards.
- Obsidian — Long-term home for the notes NotebookLM analyses.
Alternatives to notebooklm-py
- Sourclip — Gemini Notebook Workspace — Bulk-import sources, organize notebooks, and export artifacts clean from NotebookLM.
- llmspy.org — Self-host access to 530+ AI models across 24 providers with built-in tools.
- Paper2Agent — It enables direct interaction with research papers and automatic result reproduction.
- Jupyter AI — Connects frontier AI agents directly to JupyterLab notebooks.
- LLM Graph Builder — It constructs Neo4j graphs directly from unstructured data sources using LLMs.
- PaperLeet — Practice implementing 89 Python exercises derived directly from AI research papers.
- Deepnote — It combines notebook-based exploration with built-in data integrations and team collaboration.
- Lune — Accesses trusted knowledge from top conference papers for AI agents.
- Yila AI — It connects directly to trusted scholarly databases for verified literature searches.
- ObsidianYouTubeSync — Automates YouTube history syncing, transcription, and AI-powered knowledge graph creation.
- Lemma — Read mathematics with interactive proofs, reference links, and checked derivations.
- LLM Stats — Independent rankings updated continuously from live API metrics.
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