Email Verifier CLI/Library

Hacker News

friend and i were curious what's actually involved in email verification services like usebouncer.com. turns out the basics aren't that complicated. vibe coded a simple npm package in (mostly) one shot that does: - syntax validation - mx record lookup - smtp mailbox check (without sending emails) - catch-all domain detection npx email-reachable user@example.com https://github.com/yolodex-ai/reachable works as a library too: import { verifyEmail } from 'email-reachable' const result = await verifyEmail('user@example.com') bouncer probably does way more, feedback welcome.

Visit product View on Hacker NewsNov 25, 2025

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Actual performance

2points

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

73%73% 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

57%57% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: way · Missing: mobile apps, ios, personal

50%50% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

32%32% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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