SwitchBoard – route macOS links to different browsers/profiles by app

Hacker News

I built this because macOS lets you set one default browser, and I use three. Links from Slack kept opening in Safari. Terminal links opened outside my dev browser. The copy-paste workaround got old. SwitchBoard registers as your system default browser, intercepts clicked links, and routes them by rule: - App rules: Slack → Chrome Work, Xcode → Firefox Dev Edition, Messages → Safari - Domain rules: zoom.us → Zoom desktop app, figma.com → Figma desktop app - Profile targeting: specific Chrome/Arc/Firefox profiles, not just the browser The main alternatives are Choosy ($10) and Velja ($8). Both are solid. SwitchBoard differs in a few ways: it has a free tier, it supports Arc Spaces (which neither handles natively), and it includes cloud sync for keeping rules in sync across multiple Macs. It's also outside the App Store, which means direct binary launch for profile targeting without sandboxing constraints. Built in Swift/SwiftUI, runs in the menu bar, ~10MB RAM. URLs never leave the machine — the only outbound call is a version check against a GitHub Gist. Core routing is free. Profile targeting and cloud sync are in the $14.99 one-time Pro tier. Happy to answer questions about the routing logic or the Apple Event handler approach — that part was more interesting to implement than expected.

Visit product View on Hacker NewsJun 25, 2026

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

87%87% 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 · Missing: reddit linkedin, podcasting, created

79%79% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

41%41% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

30%30% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

24%24% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

19%19% 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.

Correct prediction on native model

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