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Accept.md now supports SvelteKit – return Markdown from any page

Hacker News

Accept.md now supports SvelteKit – return Markdown from any page

A few days ago I shared accept.md, a small utility that lets a Next.js page return Markdown when the client sends: Accept: text/markdown Instead of HTML. No one asked for SvelteKit support, still I shipped it. It now works with: * Next.js (App Router and Pages Router) * SSG / SSR / ISR * SvelteKit routes * Vercel (no custom server required) What it does: If a client sends: Accept: text/markdown The exact same page returns clean Markdown. If not, it behaves normally and renders HTML. No duplicate routes. No separate .md files. No API layer. No SEO changes. Just proper HTTP content negotiation. Why I built this: LLMs prefer Markdown. Internal tools prefer Markdown. Scrapers prefer Markdown. CLI workflows prefer Markdown. But most sites only return HTML. The usual solutions are: * Maintain a parallel Markdown version * Build a custom export route * Create a docs API * Spin up a custom server That felt unnecessary. Browsers already send Accept: text/html. Agents can send Accept: text/markdown. HTTP already solves this. Accept.md just makes it easy to use content negotiation inside modern frameworks without breaking static generation or edge deployments. Design goals: * Zero UI changes * Zero runtime cost for normal visitors * Works with static builds * Cache-friendly * Framework-native It’s intentionally small. No heavy abstraction. Just a clean way to expose Markdown representations of existing pages. Would love feedback — especially from people building AI-native apps, documentation systems, or content-heavy SaaS. Curious whether Markdown negotiation becomes more common as agents become first-class web clients.

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Product HuntOn track for Day 1 leaderboard · Strong signals: agents, agent, apps · Missing: mac, macos, cursor
95%95% 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: supports, para · Missing: reddit linkedin, podcasting, created
87%87% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: friendly · Missing: plus, platform, intuitive
33%33% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: apps, way, para · Missing: mobile apps, ios, personal
30%30% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: saas · Missing: arr, mrr, revenue
30%30% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: exist, existing, ide · Missing: https docs, excited, just released
28%28% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
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.

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