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Grap – A self-hostable temporary email service

Hacker News

Grap – A self-hostable temporary email service

It's a simple, self-hostable system for managing temporary email addresses, designed specifically for developers and automation workflows. I built this primarily for my own use to be able to run full integration tests for projects that rely on email confirmation etc., but I'd love to get feedback from the HN community. What features would make this more useful for your workflows? Key features: - REST API for generating addresses and retrieving emails - Web interface for manual management - Lightweight SMTP server - Docker-ready for easy deployment The entire backend is written in TypeScript and uses Fastify, Knex, and Objection.js. The frontend is intentionally minimal, using Liquid templates and vanilla JavaScript to keep things fast and simple. The project is MIT licensed, so feel free to fork and modify as needed. There's also a live demo at https://grap.email if you want to try it out before deploying your own instance.

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
85%85% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: dock, email, using · Missing: mac, agents, macos
81%81% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoStrong fit for a featured deal · Strong signals: host, interface · Missing: plus, platform, intuitive
58%58% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
57%57% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
35%35% 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
15%15% 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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