Mencrouche – A Hackable On-Demand Homepage

Hacker News

I loved Markdown New Tab (a web extension that open an editable markdown page on new tab) but wanted to add widgets like weather, which it couldn't do since extensions can't execute userscripts. So I built Mencrouche, a hackable homepage where you can add bookmarks, markdown notes, images, or any custom widget by just pasting code into custom JS textarea. No cloning repos or installing anything. While building this, I try not to use frameworks like React and found it's actually easier to manage state with plain variables and direct DOM manipulation. I ended up writing my own libraries for translation, DOM aliases, and undo/redo. Currently it's just a web page since I'm struggling with manifest V3 for the web extension version.

Visit product View on Hacker NewsJul 27, 2025

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Actual performance

2points

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Launch Intel predictions

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

93%93% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

71%71% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

45%45% 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, widgets · Missing: mobile apps, ios, personal

41%41% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

31%31% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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