Weejur – Paste HTML to Publish for Free with GitHub Pages

Hacker News

Hi HN - I know this community isn't the target user for this tool, but I think there are some likeminded folks here. There's been a lot of recent discussion here and in other tech communities about encouraging people to make their own websites and advocating for the "small web" (e.g. [1], [2], [3]). A common point in these discussions is that most people don’t have the technical skill or motivation to make their own website. These days, LLMs and AI tools have made it easier than ever for anyone to make a website, even without using a drag-and-drop builder. But there are still too many barriers for your average non-technical person to publish a site on the web. I'd bet most people don't know there are free ways to host a website, and even if they find an explainer, technical platforms like Cloudflare and GitHub (let alone the command line) can be intimidating. So I made weejur, which is basically a super simple UI front-end for GitHub Pages. You log in with OAuth, and then you can just paste HTML or upload files to publish a website. If you don't have a GitHub account, you can sign up right in the OAuth flow. It's completely free, and you can view the source here [4]. My hope is this makes it easier for people who don't know anything about web hosting to create and share their own websites. Feel free to try it out and please share any questions/ideas/feedback! [1] https://news.ycombinator.com/item?id=47421442 [2] https://news.ycombinator.com/item?id=46457784 [3] https://news.ycombinator.com/item?id=47410542 [4] https://github.com/weejur/weejur/ (Note: I'm not affiliated in any way with GitHub.)

Visit product View on Hacker NewsMar 31, 2026

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

83%83% 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

75%75% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

75%75% 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: platform, host, builder · Missing: plus, intuitive, reviews

45%45% 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 · Strong signals: arr · Missing: mrr, revenue, profit

12%12% 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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