SharePad – share a USB iPad as a clean window in any call
Eliminates the QuickTime dance for sharing iPad screens in Zoom calls.

Point-and-talk UI beats prompt engineering by streaming screenshots on speech pauses.
Frontend developers, no-code builders, rapid prototypers
Cursor · Replit Agent · v0.dev
- Video demo: https://youtu.be/RteRVM7BSps - Github URL: https://github.com/abi/1-800-CODER
How is pointing implemented? GPT-Realtime-2 only supports image inputs (unlike Gemini Live which also supports video inputs). So, the app sends a screenshot including the cursor when the model emits a speech_stopped event. That way, the agent always has a fresh visual before it replies.
Limitations:
- GPT-Realtime-2 is okay at front-end changes, probably at a GPT-4o level. Small modifications like copy changes, adding/removing elements, formatting updates work really well at low latency. In fact, for these types of changes, this might be my ideal interface. But if you wanted this app to be more useful for larger changes or generating UI from scratch, you’d want to hook up a subagent system that runs a smarter model like GPT 5.5 or Claude Opus. - GPT-Realtime-2 is expensive. The good news though is that bandwidth is really high here so you might save time with this interface.
Eliminates the QuickTime dance for sharing iPad screens in Zoom calls.
Plug any OpenAI-compatible provider into a single UI, switch models mid-session, and run side-by-side comparisons while tracking usage — everything you'd expect from a multi-model chat client. The design is eye-catching and the web/desktop split suggests a real app, but this is a crowded niche; the product will live or die on stability of provider integrations, context/memory handling, and clear privacy controls.
Rich inline charts and maps beat Claude Desktop's text-only responses.
Native macOS client replacing the sluggish App Store Connect web UI with local AI.
Native Mac batch editor that keeps 2000 wedding photos off the cloud.
The project is a pragmatic, no-friction way to route MCP client output to macOS TTS — you get a runnable speak_server.py, ready-made CLI snippets for Gemini and Claude, and persona profiles that alter spoken behavior. Small but thoughtful extras like dynamic AGENTS.MD and persona presets make it useful for prototyping voice-first agents. The downside is obvious: it’s macOS-only and targets a narrow audience, but for that audience it removes a lot of friction.