Bloggr – a Next.js blogging engine (open-source; MIT)

Hacker News

Hi HN! I’m excited to open-source Bloggr, a lightweight, Next.js-first blogging engine backed by Supabase (by default). # Repo: https://github.com/Antibody/bloggr # Blog demo: https://bloggr.dev/blog Key Features: a) Modern Next.js 15.3 App Router foundation; b) Secure admin area (CRUD) with Supabase auth & middleware protection; c) Tiptap rich text editor with image uploads (to Supabase Storage Bucket); d) Blog index pagination; e) Per-post SEO tags TODO: a) Add themes; b) Add blog posts and blog index layout customisation; c) Add other data layers; Feedback Welcome: What features are crucial for your blogging needs? What other data layers (PostgreSQL direct, MongoDB) would you like adapters for? Thanks for feedback and for checking repo out! P.S. Node.js version is coming soon

Visit product View on Hacker NewsApr 23, 2025

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

67%67% 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: excited, io · Missing: https docs, just released, exist

59%59% 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

47%47% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

35%35% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

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

21%21% 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

3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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