PocketDog

PocketDog is a mobile companion app for ArchiveBox, designed to let you read your archived articles on the go.

Why PocketDog?

I created PocketDog because I wanted an easy way to access and read my ArchiveBox-archived articles from my phone, even when offline. ArchiveBox is great for archiving web content, but there wasn't a simple, mobile-friendly way to browse and read those saved articles—especially the clean, reader-friendly versions generated by Mercury.

PocketDog solves this by connecting to your ArchiveBox instance, downloading the Mercury-processed HTML files, and saving them to your device for offline reading.

Features

• Connect to your ArchiveBox instance (API key required)
• Fetch and download archived articles (Mercury HTML)
• Read articles offline in a clean, mobile-optimized view
• Mark articles as read/unread
• Delete individual or all articles from your device
• Simple, modern UI

How It Works

1. Configure your ArchiveBox API URL and API key in the app's Settings.
2. Fetch your archive: The app will connect to your ArchiveBox server, list your archived articles, and download the Mercury HTML files for offline reading.
3. Read anywhere: Browse and read your saved articles, even without an internet connection.

Requirements

• An ArchiveBox instance v0.8.0 or newer
• ArchiveBox API functionality enabled (see ArchiveBox docs)
• Mercury content extraction enabled in ArchiveBox
• iOS device (tested on iOS; Android support coming soon)

Getting Started

1. Clone this repo and install dependencies:

   yarn install
   

2. Run on iOS:

   cd ios && pod install && cd ..
   yarn ios
   

3. Open the app, go to Settings, and enter your ArchiveBox API URL and API key.
4. Fetch your archive and start reading!

Notes

• Only tested on iOS so far. Android support is planned.
• This app downloads and stores the Mercury-processed HTML files for each article, so you can read them offline.
• No personal data or API keys are stored in the codebase; all sensitive info is kept on your device only.

License

MIT

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This app was made with the help of AI (AI slop).