developer-tools chatgpt data-export ai-agents

Free way to get your data out of ChatGPT Business accounts

GitHub - Conradqh/scrapemychats: Export a ChatGPT account (incl. business/Team) to a local searchable offline archive - conversations, files, and a single-file HTML viewer

github.com

July 23, 2026

7 min read

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48/100

Summary

scrapemychats is a tool that allows users to export ChatGPT business and Team account conversations, including text and attached files, to a local searchable offline archive. It creates a single-file HTML viewer for easy access to the exported data.

Key Takeaways

The scrapemychats tool allows users to export ChatGPT conversations and files from business and Team accounts to a local offline archive.
The exported data includes a searchable HTML viewer, conversation transcripts, and all attached files, ensuring data remains on the user's machine.
The tool operates through a real Chrome window using the user's logged-in ChatGPT session and does not transmit any passwords or data externally.
Users need Python 3.10+ and Google Chrome to run the tool, which requires a setup time of about 20 minutes before the export process can run unattended.

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Coverage & discussions

Hacker News · github.com

Free way to get your data out of ChatGPT Business accounts ↗

Community discussions

Hacker News discussion ↗

Historical count: 5 · 5 saved in sample · Historical sample

Analysis ready

Community Sentiment

Mixed

Positives

Contributors are stepping up with creative solutions to export data from ChatGPT Business accounts, showcasing community ingenuity in overcoming platform limitations.
Several users express gratitude for the shared tool, emphasizing its practical utility for retrieving important data.
The tool's ease of use, highlighted by users, demonstrates a growing trend towards accessible solutions in AI-driven applications.

Concerns

The lack of a straightforward data export option from ChatGPT Business accounts frustrates many users, indicating a significant oversight in user experience design.
Comments reveal a missed opportunity for more efficient methods, suggesting that current solutions are only temporary workarounds rather than proper fixes.