Markpad – The Notepad Equivalent for Markdown

Hacker News

Built this for two reasons: One: I've always wanted to be able to double click a Markdown file and see it like it appears on GitHub. Didn't want Obsidian or jumpy VS Code extensions just to view a README offline. Two: Opening Microslop's Notepad lately shows how determined they are to add bloat to every aspect of Windows, so I needed a replacement. Markpad is a simple Markdown file viewer and general text editor, rendered as close as possible to GitHub's markdown flavor. Features: - Tabbed interface - Monaco editor (VS Code) - Syntax highlighting both in editor and code blocks - Image and YouTube embeds - Familiar GitHub styled markdown rendering - Tiny memory usage (~10MB) - No telemetry or bloat - Free and open-source - Lightweight native-feeling UI Still in development, so I'd love some feedback on how to shape it to something more people can enjoy. Cheers

Visit product View on Hacker NewsJan 28, 2026

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5points

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: tiny, code, open · Missing: mac, agents, macos

91%91% 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.

Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released

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

nativeThis product was originally launched on this platform.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

44%44% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

40%40% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

31%31% 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

20%20% 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.

Incorrect prediction on native model

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