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Magic Input – Use your iPhone as a keyboard and trackpad for your Mac

Hacker News

Magic Input – Use your iPhone as a keyboard and trackpad for your Mac

Hey HN, On a recent flight home for Christmas, I tried to get some side-project work done on my MacBook… and immediately lost the battle with Seat 28C. I could barely open the laptop, let alone type comfortably. The real constraint on planes these days is elbow room. That got me wondering: could a small, handheld keyboard and trackpad setup make in-flight work tolerable? After failing to find anything compelling on Amazon, I realized something obvious: my iPhone already has a great keyboard and touch experience. So why not use it directly? I looked for existing apps, but the top options felt dated and required both devices to be on the same Wi-Fi network—which isn’t always possible (or desirable when paying ridiculous prices for airplane Wi-Fi). So over the last few days I’ve been tinkering with a project I call Magic Input. It turns your iPhone into a wireless keyboard and trackpad for your Mac. How it works (high level): • The iOS app discovers nearby Macs using MultipeerConnectivity • Keyboard input and touch gestures are streamed directly to macOS • The macOS app injects events at the system level (requires Accessibility permissions) • No shared Wi-Fi network required; devices connect peer-to-peer It’s very early, but already supports basic typing and cursor control—especially useful in cramped spaces like planes. Here’s the TestFlight link for the brave. You’ll need to install the same app on both macOS and your iPhone: https://testflight.apple.com/join/T1PgucDs Happy to answer questions or dig into implementation details if anyone’s curious.

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: mac, macos, cursor · Missing: agents, agent, claude
97%97% 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, ios · Missing: reddit linkedin, podcasting, created
97%97% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: exist, existing, ide · Missing: https docs, excited, just released
55%55% 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 · Strong signals: ios, apps, way · Missing: mobile apps, personal, entrepreneurs
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
35%35% 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
16%16% 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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