LocalModelsLinks collects guides and references for running and tuning language models locally.
Screenpipe
Screenpipe records screen activity locally and provides context to AI agents.

About Screenpipe
Screenpipe continuously records computer screen and audio work and stores it locally to provide context to AI agents. It maps workflows to identify work worth automating and can generate agents, skills, and automations based on observed activity.
It includes natural-language search across captured history, accessibility-tree capture with OCR fallback, audio transcription with speakers, and tracking of keyboard inputs and app switches. Local capture and search work offline after setup. Cloud AI, sync, integrations, and managed team storage use separate data paths and require network access. Available features depend on plan, and the desktop app is offered for macOS, Windows, and Linux.
Key features
- Records screen and audio activity to local storage by default
- Maps computer workflows to identify tasks worth automating
- Searches captured history using natural-language queries
- Captures accessibility tree with OCR as fallback
- Transcribes audio with speaker and app-switch tracking
- Filters recording by app, window, passwords and PII
- Local-first storage keeps capture history on device by default
- Local capture and search work offline after setup
- Source-available code can be inspected and audited
- Available features depend on plan
- Capture uses approximately 5-20% CPU and 0.5-3 GB RAM
- Storage use varies and requires measuring a representative day
Screenpipe at a glance
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Not stated
- Language
- English
- Last checked
- Oct 5, 2026 · Online when checked
- Listed
- Oct 5, 2026
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Screenpipe FAQ
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