Pinakes – Open-source library system with built-in public catalog

Hacker News

Pinakes is a self-hosted library management system. Upload files to any PHP/MySQL host, run the installer, start cataloging. What it does: - ISBN scraping auto-fills metadata from Open Library, Google Books, and European library catalogs. Adding a book takes seconds. - Full circulation: loans, returns, renewals, reservations with FIFO queues, automatic email reminders for due dates and overdue books. - Multi-copy support with barcodes. Dewey Decimal preloaded (1,369 categories). CSV bulk import. - Public catalog with search, patron self-service (renewals, reservations, wishlists), reviews and ratings. - Interactive calendar with ICS export for syncing loans to Google Calendar/Outlook. - CMS with homepage editor, 10 color themes, custom pages. - eBook/audiobook support with streaming player. - SRU protocol for interoperability with other library systems. - Plugin architecture for custom integrations. Stack: PHP 8.1+, MySQL 5.7+, Slim 4, vanilla JS. To try: clone repo, run `php -S localhost:8000 router.php`, open browser. GPL-3. No telemetry. Looking for testers and contributors.

Visit product View on Hacker NewsNov 30, 2025

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

78%78% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Product HuntOn track for Day 1 leaderboard · Strong signals: google, new, email · Missing: mac, agents, macos

61%61% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: google · Missing: mobile apps, ios, personal

42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: reviews, host · Missing: plus, platform, intuitive

34%34% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: 000, io · Missing: https docs, excited, just released

33%33% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue

21%21% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: audio · Missing: web3, chat, crypto

7%7% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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