Alexandrie – A open source Markdown note-taking app I built as student

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Hi HN, Over the past few years, I’ve been working on a personal project called Alexandrie, a web-based Markdown note-taking app that started as a tool I built for myself while in engineering school. I wanted something fast, offline-friendly, and minimal, without the heaviness of tools like Notion or Obsidian — but still with enough structure and features for everyday note-taking and writing. After a lot of iterations, I’ve just released version 8.0.0, which includes major improvements to the documentation, Docker setup, and overall performance. Key features: Extended Markdown syntax (snippets, instant formatting, keyboard shortcuts) Offline-first (works even without a connection) Categories, workspaces, and sub-doc organization Simple Go backend + Vue/Nuxt 3 frontend Fully open source under MIT license Why I’m sharing this I’m not launching a product — this is more of a community project that I’d love to keep improving with other developers. I really enjoy discussing ideas, reviewing PRs, and getting feedback from people who use or hack on similar tools. If that sounds interesting, you can check out the repo here: https://github.com/Smaug6739/Alexandrie There’s also a hosted demo version you can try directly in your browser. Any feedback, ideas, or suggestions are very welcome! Thanks for reading

Visit product View on Hacker NewsOct 25, 2025

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

87%87% 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 · Strong signals: started · Missing: supports, reddit linkedin, podcasting

66%66% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: just released, open source, ide · Missing: https docs, excited, exist

63%63% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

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

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

32%32% 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

11%11% 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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