64K Tools – 50 browser-based tools, no signup required

Hacker News

Hi HN, I built 64K Tools – a collection of 50+ free utilities for both developers and everyday users. Developer tools: - JSON/XML/YAML formatters - Base64/URL encoder/decoder - Password generator with strength checker - Hash generators (MD5, SHA, etc.) Everyday tools: - QR code generator - Weather app - Calculator - Unit converters - Live world statistics (births, deaths, CO2 emissions, etc.) - Random cat gallery (for stress relief!) Key features: - Star your favorite tools (stored locally, no account needed) - All processing happens in browser (privacy-first) - Available in 18 languages - Works offline after first load Tech stack is simple: PHP for templating, vanilla JavaScript, no frameworks. Hosted on Nginx. Would love your feedback and suggestions for new tools!

Visit product View on Hacker NewsJan 26, 2026

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

64%64% 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.

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

48%48% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

36%36% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

26%26% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: user, new, code · Missing: mac, agents, macos

12%12% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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