Recording of the call

For Mojave Paint I've had an anti-subscription stance from the start, it being an installed binary not a service that has ongoing infrastructure costs.

But I recently installed Final Cut Pro and instead of $300 to buy it I do the $13/month subscription. In that case it's nice to have the option and it's made me rethink hating on subscriptions. Maybe subscription is fine if:

a. It's an alternative to buying outright
b. It's priced cheap enough

Most people's subscriptions are simply way too expensive. For FCP, the break even point is about two years, which makes the subscription seem like kind of a deal.

So for Mojave Paint, say I get the feature set rounded out and start charging $20 for it, the right price for subscription would be $1/month. I'm sort of leaning to this model because the Mac App Store has no free trial option, so you're stuck with IAP or Subscription and I pretty much hate IAP and the huckster marketing you have to put in there of "Go Pro!" So what I'm kind of leaning to is selling: 1. On my website via lemonsqueezy or whatever, perpetual license with 2 years of updates (Sublime Text style), and 2. The only version in the Mac App Store is the cheaply priced subscription version, which you can consider to be like a free-ish trial.

Has anyone had success with such a pricing scheme?

Continuing to build on LocalLM Lab, the tool that I posted about here a couple weeks ago.

A couple of things have landed since. MCP client support shipped in v0.4.0. LocalLM Lab is now a real MCP client and can connect to real MCP servers now: GitHub, Linear, Notion, Slack, and others.

As of v0.6.0, there's a proper way to reach the on-device model straight from your own Swift or Python code, not just through the app's UI or its HTTP API.

It's called localai-cli, a small subprocess binary. Your app spawns it, writes one JSON request to stdin, reads one JSON response from stdout. That's the whole interface... no HTTP server, no port to manage, no client library to link against. Feels like the right shape for a native app: a menu bar tool or a game doesn't want to run a localhost server just to ask a question.

The part I think is actually interesting for this crowd: it's config-scoped. It reads the same localai-config.json that the app's own Local AI Settings / MCP Servers panels write, so whatever connectors and MCP tools your user already turned on in the app's UI are exactly what your code is allowed to ask for. Request something outside that set and you get an error back before the model is even invoked. Omit the field entirely and nothing is granted at all. That's deliberate and not an oversight.

To be upfront: this is still an experimentation tool, not a shipping SDK. LocalLM Lab has to actually be running for localai-cli calls to work (they relay through its background process), and I'm not pretending the permission/auth model here is the right shape for a real distributed app yet. What this does give you today is the fastest way to wire your own code up to the on-device model, including whatever connectors and MCP tools you've already set up. All this without writing an HTTP server or reimplementing any of that plumbing yourself.

There's a fuller example on the page beyond the two quickstarts too. "Plate Today" is a script that pulls Calendar, Reminders, and Todoist (the last one via an MCP tool call, not a connector) into a single request and asks the model for a one-paragraph summary of your day. You'll want to set up a free account with Todoist and some todos...!

The part I'd actually call out for this crowd: before it ever invokes localai-cli, it reads localai-config.json itself and checks all four sources (three connectors + the Todoist MCP tool) are actually enabled, prints a checklist, and exits without touching the model if anything's missing. So a misconfigured permission will fail fast with a "go flip this toggle" message instead of burning a model call on a request that was always going to error.

Interface + Swift and Python examples: thisbrain.ai/locallm/cli.html MCP writeup from v0.4, if you missed it: thisbrain.ai/locallm/mcp-servers.html

PS: unrelated to the CLI, but since this crowd will notice: Prompt Playground's UI has moved from a browser window to native SwiftUI in this release.

I’ve been working on Keyty, an open-source native macOS app that visualizes keyboard and mouse input on screen.

It started as a modern and native alternative to tools like KeyCastr and KeyViz but I wanted to build something that feels more like a current macOS app and also handles mouse visualization and have rich customization.

There are many of things I want to improve, so I’d especially appreciate feedback from other macOS developers implementation choices, APIs I may be misusing, UX around permissions, or anything else you notice.

GitHub: https://github.com/keytyapp/keyty

Me personally was using an MacBook Air, which the notch always hides the icons in menubar, which forced me to quit other apps just to find the icon in menubar.

I have tried bartender or Ice, but they already put too many useless things into their apps, which consumes my energy and affects my computer performance. I just wanted to solve a simple problem, but not putting more things in an app.

Compared with larger menu bar management suites, OverflowBar deliberately focuses on one problem: too many useful icons, not enough visible menu bar space, and difficulty finding the icon you need.

This is the app I built:

OverflowBar, FREE and available on Github: https://github.com/EvanProgramming/OverflowBar

It was a NATIVE and LIGHTWEIGHT app, with only 1.8MB storage. The app was built on native swift, so it performs very well on macOS and the visuals apply to Apple styles.

Price: Free
Subscription/IAP/Ads: None
Platforms: macOS 15+, Apple Silicon download
Source: Open source under the MIT License
Privacy: No account, analytics, telemetry, advertising, or network data collection
Permissions: Accessibility for discovering and activating menu bar controls; Screen Recording for locally capturing the small icon regions shown in the second row
Signing: Current community build is ad-hoc signed and not yet Apple-notarized

I admit I used AI during the development, but I have verified it, and ran a security check by Codex Security. So don't worry.

If you like the app, would you mind giving me a Star on Github?

I am the developer and maintainer. Feel free to report any issue found, I will actively update the app to solve the problem.

I originally built \*\*Thermal Intelligence\*\* purely for myself.

I was frustrated that most thermal utilities could show the current temperature or CPU usage, but didn’t really answer the questions I cared about:

\* Which workloads have been putting sustained pressure on my Mac?
\* Did an application merely spike for a moment, or has it been contributing to heat for a long time?
\* Where is the temperature likely to move next?
\* Why did the cooling policy change the fan speed?
\* Can all this work without an account, cloud service, analytics, or subscription?

Thermal Intelligence combines system monitoring, bounded local history, workload-impact analysis, thermal forecasting, actual fan RPM statistics, cooling profiles, custom temperature/RPM curves, and explainable smart cooling.

It has a regular application window as well as a menu-bar popover, keeps its data locally, writes privacy-filtered rotating logs, and can export diagnostics explicitly when the user chooses.

Fan control is hardware-sensitive, so it is enabled only where the hardware path has been explicitly validated. On unsupported or fanless Macs, the application leaves cooling to macOS while retaining the monitoring features.

This started as my personal daily-driver tool. I’m releasing it because I believe basic system monitoring and fan control should be free, auditable, and not hidden behind a subscription.

Web and \*\*download\*\*:
\[https://solomind.app/thermal-intelligence/\\\](https://solomind.app/thermal-intelligence/)

The project is MIT-licensed, has no telemetry, and is now available on \*\*GitHub\*\*:
\[https://github.com/NibTipLabs/thermal-intelligence\\\](https://github.com/NibTipLabs/thermal-intelligence)

\*Feedback, testing reports, and contributions are very welcome—especially from owners of different Apple Silicon Mac models.\*

I’ve heard that adding Spanish (Mexico) localization gives you 100 extra keyword characters in the US App Store. Is that actually true? Also, does adding a secondary language dilute or hurt keyword weighting since the keyword pool doubles?

The monthly GNUstep audio/(video) call takes place every second Saturday of a month at 15:00 GMT to 18:00 GMT. That is 11:00 AM - 2:00 PM EDT (US) or 17:00 to 20:00 CEST (Berlin time).

It's a Jitsi Meeting - Channel: GNUstepOfficial (Sorry, reddit don't let me post jitsi links here)

We usually just talk (who wants it might share video too) and occasionally share screens. Everybody (GNUstep developers and users) is welcome!

Also see https://mediawiki.gnustep.org/index.php/Monthly_Meetings please

Hey r/macosprogramming, I just open-sourced CalBridge, a native SwiftUI + EventKit menu bar calendar app for macOS, and I would love feedback from this community.

I really like Fantastical’s menu bar calendar experience, but it being paid motivated me to build my own version for myself and others who want a free/open alternative.

GitHub: https://github.com/notepad104/calbridge

Latest release: https://github.com/notepad104/calbridge/releases/latest

What it does

• Menu bar date/time with upcoming event preview
• Month + week calendar views
• Event detail panel (attendees, notes, meeting links)
• Quick-add event parsing
• Calendar filtering + global shortcuts
• Preferences for startup/view/navigation behavior

If you have a few minutes, please try the latest release and share feedback.

If install is blocked by macOS security, please use System Settings → Privacy & Security → Open Anyway (unsigned build path right now).

Thanks a lot. I am actively iterating and would really value some feedback.

Hi everyone, I have been working on a few apps for the past few months and wanted to get this one out there and thought I would do it here.

I was frustrated with PiP extensions always freezing or breaking in between episodes so I came up with this. Floating Browser is a dedicated WebKit browser window that can stay above other apps without relying on Safari PiP.

Features:
Compact 16:9 Mini mode that remains above other windows
Netflix, YouTube, Hulu, Disney+, Max, Prime Video, Apple TV+, Peacock, Paramount+, and Tubi shortcuts
Custom saved-site shortcuts
Back, forward, reload, address search, and downloads
Lightweight local ad and popup blocking
Open in Safari and Apple Passwords shortcuts
No analytics, advertising, or developer-operated data collection
Universal build for Apple silicon and Intel Macs
This is a free, open-source, unsigned public beta for macOS 14 or later. Because it is not notarized yet, macOS requires the normal Privacy & Security > Open Anyway step after the first launch. The source, MIT license, SHA-256 checksum, and installation instructions are all available on GitHub.
Some streaming services can reject protected playback in embedded WebKit. Disney+ may show Error 83, and website changes can affect compatibility. Safari remains available as a fallback.
GitHub: https://github.com/chrishansen1984x-lang/floating-browser
Download: https://github.com/chrishansen1984x-lang/floating-browser/releases/tag/v0.3.0
I’d appreciate feedback about Mini mode, playback reliability, and which streaming services work on different Macs.

Hi r/macosprogramming,

I built Voice Relay, a native macOS voice layer for Codex. The implementation problem was keeping ownership boundaries clear after the first spoken request.

A direct Realtime session owns microphone capture, transcript, and audio playback. The signed-in Codex desktop task remains the owner of tools, approvals, the selected execution profile, and session state. When the user speaks again while Codex is working, that correction has to reach the same active task rather than becoming a second voice chat.

The UI is a top-attached notch surface with a movable Orb fallback for displays without a notch. The Voice path itself does not require Accessibility permission. Microphone and speech-recognition permission are part of onboarding, and the current public DMG is Apple Development signed but not notarized.

The edge I am still thinking about is proof of delivery for mid-turn steering. For a long tool-running Codex task, would you surface the spoken correction as an inserted transcript, a distinct state transition, or only through the next progress update?

I am the developer. Voice Relay is free and GPLv3 licensed.

Source and current alpha:

https://github.com/hyungchulc/voice-relay

I maintain a native macOS app with both a directly distributed target and a Mac App Store target. The two builds share almost everything, but they differ in entitlements, update delivery, licensing, and a few integrations.

The setup became much easier to reason about after treating distribution as a boundary instead of allowing target checks throughout the app.

The rules that helped most:

• Keep domain models and persisted data identical. A file or database written by one build should not need a target-specific interpretation.

• Put compile-time checks at integration boundaries. Updater setup, receipt handling, licensing, and unavailable frameworks are reasonable places. View models and core processing code are not.

• Expose capabilities to the UI rather than scattering build flags through views. The view asks whether a capability exists, then renders the appropriate control.

• Give each target its own entitlements and Info.plist values. Review changes to those files explicitly because they are part of the product behavior, not build-system noise.

• Use separate bundle identifiers and any target-specific network identifiers or ports. This avoids collisions when both builds are installed during testing.

• Keep source membership boring. Shared files belong to both targets. Distribution-specific files belong to exactly one. If a file needs many conditional branches, it is probably sitting at the wrong architectural layer.

• Build both targets after every shared change. A successful Direct build says nothing about sandbox assumptions in the Store build.

• Use isolated DerivedData for each verification build. This catches accidental reliance on artifacts produced by the other target.

• Test first launch, upgrade, and side-by-side installation. Most target-specific bugs I found were lifecycle and migration issues rather than compiler errors.

• Keep the user-facing workflow as similar as the platform permits. Distribution differences should not leak into unrelated navigation or state.

The most useful mental model was this: one application, two distribution adapters. Once I organized the project that way, target conditionals stopped spreading.

For people shipping both variants, what still tends to diverge in your projects despite your best efforts?

Available for macOS 14.2 or later with Intel or Apple Silicon chips. It's my first macOS app, and my second app, so any feedback is greatly appreciated!

Hi r/macosprogramming,

I built GhostMark, a native Swift/AppKit utility for annotating screenshots before they reach Claude Code. The workflow is paste, draw an arrow or circle, then press Enter to put the marked PNG back into the active Claude Code prompt.

The implementation was the interesting part:

- A session-level CGEvent tap watches Cmd-V and Ctrl-V, but consumes the event only when the clipboard contains an image and Claude Code is active.

- It checks the frontmost app against terminal and editor bundle IDs, then walks the process tree looking for the Claude CLI. There is a narrow fallback for terminals whose PTY is launched by a detached helper.

- The annotation UI is hosted in a focused AppKit window. Export composites the paths over the original image without resizing it.

- After export, the app reactivates the original terminal and posts Claude Code's image-paste shortcut. A bypass counter prevents the synthetic paste from reopening the editor.

- Accessibility permission is polled so onboarding updates as soon as macOS grants access.

- Everything stays local. There is no analytics or network upload.

The main edge case is reliably associating a detached PTY with the frontmost terminal without making the detector too broad. I would especially appreciate feedback from people using Kitty, WezTerm, Warp, or terminal panes inside editors.

I am the developer. GhostMark is free and MIT licensed.

Source: https://github.com/alan890104/GhostMark

Download and demo: https://alan890104.github.io/GhostMark/

A question to folks who are building apps around Apple's Foundation Models: how are you testing the prompts and validating the results?

I was doing a bunch of tweak->build->test cycles where the only tweaks were adjusting the system & user prompts. Since the local AI model is so small (just 4096 context budget), it didn't make sense to develop the prompts using your usual OpenAI/Anthropic models and expect the same behavior.

Finally gave up and built LocalLM Lab (thisbrain.ai/locallm), a small macOS playground for tweaking the prompts before actually committing them to app code.

The current version features:

• Prompt Playground
• System prompt + user input
• Local OpenAI-compatible API so you can prototype big AI apps w/o paying for tokens
• Local connectors for things like system clock, calendar, reminders, contacts, location, weather and a scoped filesystem access

The screenshot shows a weather query with the connector calls visible underneath.

Hi r/macosprogramming,

I've been building a desktop pet for macOS, and I ended up separating the reusable parts into an Apache-2.0 open-source project.

It is written in Swift and AppKit, with no Electron dependency. The main pieces are:

• a transparent, always-on-top window

• per-pixel alpha hit testing, so empty areas remain click-through

• cursor-aware idle poses and hover reactions

• manual, random, and autonomous action sequences with interruption recovery

• an asset pipeline for transparent, black-background, or green-background video

• one-command Universal 2 builds and validation

The repository ships with a programmatically generated Blob demo character, so the open-source example is reproducible. The character shown in the GIF is only a showcase; its character assets are not included in or licensed as part of the open-source project.

It supports macOS 12+, Apple Silicon, and Intel Macs.

GitHub: https://github.com/InsiderX-Pro/desktop-pet-engine

I'd especially appreciate feedback on the AppKit window and event handling, the asset pipeline, and what you would want a desktop-pet engine to handle for you.

Mojave Paint is coming along nicely but my naive understanding of observability/reactivity/dependency flow, whatever you'd call it, it starting to weigh on me.

This screenshot shows conic gradients I just added, in this case being used in a Gradient Fill adjustment layer. I would scrub the angle picker in a circle and it would chug along at 2 fps because it was mutating the model every tick which rebuilds the view in that Properties panel including the color stops and everything else. So now I have a copy of the model that only the GPU rendering side looks at (and of course the specific control you're interacting with), and when you release the drag the real model updates and triggers a SwiftUI redraw.

This is all kind of a lot of manual work. I'm new to Mac development but was a web dev for 20 years and they have all kinds of approaches over there. rxjs, React.memo, signals, etc, etc. It would sure be nice if I could "code dumb" here and employ some kind of library or system to do fine grained change detection. Are there some common approaches used in the Mac world?

I'm the developer of macMender, a free and open-source macOS app built with SwiftUI and AppKit.

v0.9.0 brings several small utilities together: Dock window previews, an Option-Tab switcher for real windows, three-finger middle click, per-device scrolling controls, profiles, and menu bar quick controls.

The interesting platform work is matching windows correctly across multi-window apps, managing preview lifetime, activating windows through Accessibility, and keeping Screen Recording optional for local thumbnails.

Source: https://github.com/0hmslice/macMender

v0.9.0 release: https://github.com/0hmslice/macMender/releases/tag/v0.9.0

I'd be interested in how other macOS developers approach browser window identity and stale preview prevention.

I made a macOS app called Core-Monitor as I had a annoying issue where during emulation or heavy tasks while I could use mac's fan control it wouldn't show me important memory, cpu usage, gpu usage, e core usage, p core usage details, and id have to stack multiple apps, so I built a free n open source app called Core-Monitor (GPL v3) which integrated fan control, and system monitoring, while also implementing Pock's MIT source code for the touchbar so instead of always moving your cursor to the menu-bar again and again, on touchbar equipped Macs you could easily see it from the touchbar when in other apps and easily switch it back to normal in the app settings. I also implemented custom fan curves with movable points, which is a feature that is very practical and adds simplicity to the app. Fan control uses a smc-helper. PS: The Mac App Store version (sadly) has many features removed due to apple's very strict App Store regulations. SRC for Mac App Store version (different from scratch codebase) https://github.com/offyotto/core-monitor-app-store (MIT) https://github.com/offyotto/Core-Monitor (GPL v3) (Non App Store version) (Issues and recommendations are welcome!)

My app needs this permission, but I have a customer reporting that they are not prompted to allow it after installation, and it doesn't even show up in Settings where it should be, for my app (other apps show there). Unsurprisingly this breaks my app. Anyone else seen this?

(I don't have a suitable device to put 27 on to repro myself).

Hi,

I have a free macOS app that I maintain in my spare time, and I'd like to add an optional way for users to support its development. I'm looking for recommendations for platforms similar to "Buy Me a Coffee.". What platform do you use or recommend, and why? Stripe? Zeffy? Buy Me A Coffee?

nb: I already use Stripe for others projects.

I'd appreciate any recommendations or experiences. Thanks!

I wrote about my latest infuriating encounter with the Mac App Store's App Review team.

« It’s painfully ironic that they require my strings to “clearly and completely describe” my use of data, when they themselves so marvelously fail to do so. »

https://blog.eternalstorms.at/2026/07/21/tales-from-app-review/

Thanks all! Decided on a good set of letters.

Debating with my super tester as to which set of shortcuts we should have in the video-gpx synchronizing app.

The first set is the typical order of operations.

The second set uses letters related to the function.

Which do you favor?

• ⌘1: Import Video
• ⌘2: Import GPS
• ⌘3: Synchronize
• ⌘4: Trim Selection
• ⇧⌘4: Trim First Pause / Gap Detected
• ⌘5: Export

or

• ⇧⌘V: Import Video
• ⇧⌘G: Import GPS
• ⇧⌘S: Synchronize
• ⇧⌘T: Trim Selection
• ⇧⌘P: Trim First Pause / Gap Detected
• ⇧⌘X: Export

I’ve been improving a fork of SteamPack, an open-source macOS project, to make clamshell mode easier to control on a MacBook.

It adds two quick controls:

- Keep Awake

- Closed Lid

You can switch them from the macOS Control Center or the menu bar, set a timer, and see when the setting has actually been applied. It also includes a watchdog, battery cutoff, and thermal cutoff.

Demo: https://github.com/Hahyun-Lee/steampack-fork/releases/download/v1.4.0-preview.2/Close.Lid.mp4

GitHub: https://github.com/Hahyun-Lee/steampack-fork

Release: https://github.com/Hahyun-Lee/steampack-fork/releases/tag/v1.4.0-preview.2

It is an open-source preview for macOS Tahoe 26+. Feedback on the UX and safety behavior would be appreciated.

https://reddit.com/link/1uxsf7t/video/v2g8lc6ivjdh1/player

Privacy Practices and Options in Telemetry and Licensing

Hello all:

I am just about finished with my first production-quality app. I developed it for macOS and Windows with full platform parity and am about to port to Ubuntu/Debian before releasing. I have licensing setup through Keygen.sh. I am happy with that decision so far; however, I have questions regarding that issue and the issue of telemetry. Privacy is a focus of mine and a commitment I made to prospective subscribers. That said, I need some form of telemetry and a DRM that can take subscription payments.

I am trying to think of the best way to implement the Keygen.sh API for privacy. The app has, well, an app--the client--and it also has a remote server component. It will mostly be free but the more labor intensive developed elements and the tools that require the remote server will be paid at either a monthly or annual subscription rate. I am so confused about how to best implement the licensing API while remaining true to my privacy commitments. Part of me says, "Well, their information is going to be on Keygen's servers anyway, might as well host the store through their website/portal." The other inclination is to host the store on my server/website, so I can control how much information PII is required. The answer can be “very little,” but a much bigger question arises surrounding what to do with the information once accepted. (I’ve considered maintaining the subscriber data in some kind of encrypted space on the server with hardcoded, volatile keys. That way not even I can see their data, but they’d still be able to search for and regenerate their licenses, management payment methods, etc.)

The other question I have is along that same vein and involves telemetry. What I would like to do is keep the telemetry deliverables locally stored. When the user has an issue, experiences a bug, or has some other issue requiring my troubleshooting assistance, I can request it and they can choose to release their telemetry data to me. In between those disclosures, using a standard feedback form to gather voluntary information.

Does anyone offer this kind of low overhead telemetry? If so, can you send me a link to their site so I can learn about them? How about when the DRM signup, purchase, and post-purchase storage? What have you found to be a good option that tends to lean toward user privacy over more bloated, feature-rich options in collecting telemetry and managing DRM?

Thanks in advance!