Magpie – my self-hosted replacement for Google/Yahoo email aggregation

Hacker News

I built Magpie, a self-hosted email aggregator that pulls multiple IMAP/SMTP accounts into a single inbox. I started it because Google is dropping support for pulling emails from my Yahoo accounts (Gmailify), and I wanted a private, self-hosted solution. Key points: * Unified inbox with search and threading * Lightweight backend + modern web UI * Easy to deploy (Docker or manual) * Privacy-first, fully open source This is the baseline release and it’s meant to be simple, functional, and easy to extend. I’d love feedback, bug reports, and contributions from anyone interested in email tooling or self-hosted software. https://github.com/FynleyMsg/Magpie

Visit product View on Hacker NewsJan 31, 2026

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Actual performance

3points

1comments

Did not reach leaderboard

Launch Intel predictions

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

86%86% 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: started · Missing: supports, reddit linkedin, podcasting

73%73% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

70%70% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoStrong fit for a featured deal · Strong signals: host · Missing: plus, platform, intuitive

55%55% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

48%48% 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

17%17% 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.

Incorrect prediction on native model

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