screenpipe

screenpipe turns your computer into a personal AI that knows everything you've done. record. search. automate. all local, all private, all yours

┌─────────────────────────────────────────┐ │ screen + audio → local storage → ai │ └─────────────────────────────────────────┘

- remember everything- never forget what you saw, heard, or did
- run agents that work based on what you do- pipes are agents triggered by your work activity

npx screenpipe setup # or claude mcp add screenpipe -- npx -y screenpipe-mcp@latest

then ask claudewhat did i see in the last 5 mins?orsummarize today conversationsorcreate a pipe that updates linear every time i work on task X

- captures full accessibility tree, OCR as fallback, transcription, speakers, keyboard inputs, app switches
- 5-10% cpu usage
- 0.5-3gb ram
- ~20gb storage/month
- filters (window, app, chrome extensions, passwords, proprietary AI PII model)
- optional encryption at rest
- works offline

screenpipe is a source-available application that continuously captures your screen and audio, creating a searchable, AI-powered memory of everything you do on your computer. All data is stored locally on your device. It is the leading source-available alternative to Rewind.ai (now Limitless), Microsoft Recall, Granola, and Otter.ai. If you're looking for a rewind alternative, recall alternative, or a private local screen recorder with AI, screenpipe is the most popular option you can fully audit.

Minimum requirements: 8 GB RAM recommended. ~5–10 GB disk space per month. CPU usage typically 5–10% on modern hardware thanks to event-driven capture.

Instead of recording every second, screenpipe listens for meaningful events — app switches, clicks, typing pauses, scrolling — and captures a screenshot only when something actually changes. Each capture pairs a screenshot with the accessibility tree (the structured text the OS already knows about: buttons, labels, text fields). If accessibility data isn't available (e.g. remote desktops, games), it falls back to OCR. This gives you maximum data quality with minimal CPU and storage — no more processing thousands of identical frames.

Captures system audio (what you hear) and microphone input (what you say). Real-time speech-to-text using Whisper (Large-V3-Turbo) running locally on your device, or Deepgram for cloud transcription. Speaker identification and diarization. Works with any audio source — Zoom, Google Meet, Teams, or any other application.

On macOS 14.4+, you can exclude specific apps from system-audio capture by listing their bundle IDs in~/.screenpipe/audio-exclusions.json. Enable Experimental CoreAudio System Audio in Settings → Recording first; the picker UI only appears once that flag is on.