[ screenpipe | YC S26 ]
AI that knows what you've seen, said, or heard.
Records everything you do, say, hear 24/7, local, private, secure
---
## news
- 06/10 - **we updated our license to keep screenpipe sustainable** — more funding, more shipping, better product
- 05/29 - **we released an [alpha version of our AI PII model](https://screenpipe.github.io/screenleak/) outperforming Google, Microsoft, and OpenAI models** on computer recording data and running at 9ms on consumer device
- 05/14 - **we joined YC S26**
## what is this?
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
- **search with ai** - find anything using natural language
- **100% local** - your data never leaves your machine
- **open source** - inspect, modify, own
## install
[download the desktop app](https://screenpi.pe/onboarding) — all features, auto-updates
or run the CLI:
```
npx screenpipe record
```
then
```bash
claude mcp add screenpipe -- npx -y screenpipe-mcp@latest
```
then ask claude `what did i see in the last 5 mins?` or `summarize today conversations` or `create a pipe that updates linear every time i work on task X`
## specs
- 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
## sdk
[tauri, electron, swift sdk available today](https://github.com/screenpipe/screenpipe/tree/main/ee/sdk)
---
docs ·
sdk ·
team ·
discord ·
x ·
youtube ·
reddit
## Contributing
See [CONTRIBUTING.md](CONTRIBUTING.md) for guidelines, maintainers, and how to submit PRs. AI/vibe-coded PRs welcome!
Thanks to all contributors:
## Translations
- [日本語 (Japanese)](translated_readmes/README-ja.md)
- [简体中文 (Simplified Chinese)](translated_readmes/README-zh_CN.md)
- [Français (French)](translated_readmes/README-fr.md)
- [Español (Spanish)](translated_readmes/README-es.md)
- [Português BR (Brazilian Portuguese)](translated_readmes/README-pt_BR.md)
- [Deutsch (German)](translated_readmes/README-de.md)
Want to translate screenpipe into another language? See [`translated_readmes/`](translated_readmes/README.md).
📖 LLM reference
## About screenpipe
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.
- **Website**: https://screenpi.pe
- **Documentation**: https://docs.screenpi.pe
- **Discord**: https://discord.gg/screenpipe
- **License**: Screenpipe Commercial License (source-available; free for personal use, commercial use requires a license, see [LICENSE.md](LICENSE.md))
## Who screenpipe is for
- **Knowledge workers** who want to recall anything they've seen or heard on their computer
- **Developers** who want to give AI coding assistants (Cursor, Claude Code, Cline, Continue) context about what they're working on
- **Researchers** who need to search through large volumes of screen-based information
- **People with ADHD** who frequently lose track of tabs, documents, and conversations
- **Remote workers** who want automatic meeting transcription and notes
- **Teams & enterprises** who want to deploy AI across their organization with deterministic data permissions and central config management ([screenpi.pe/team](https://screenpi.pe/team))
- **Anyone** who wants a private, local-first alternative to cloud-based AI memory tools
## Platform support
| Platform | Support | Installation |
|----------|---------|-------------|
| macOS (Apple Silicon) | ✅ Full support | Native .dmg installer |
| macOS (Intel) | ✅ Full support | Native .dmg installer |
| Windows 10/11 | ✅ Full support | Native .exe installer |
| Linux | ✅ Supported | Build from source |
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.
## Core features
### Event-driven screen 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.
### Audio transcription
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.
```json
{ "excluded_apps": [{ "bundle_id": "com.spotify.client", "name": "Spotify" }] }
```
The exclusion list hot-reloads — edits to the file and excluded apps launching/quitting are picked up on the engine's existing 500 ms tap-rebuild loop without restarting screenpipe. Override the file path with `SCREENPIPE_AUDIO_EXCLUSIONS_PATH` for testing. Note: this requires the "System Audio Recording Only" TCC permission in System Settings → Privacy & Security → Screen & System Audio Recording.
### AI-powered search
Natural language search across accessibility-first screen text, OCR fallback text, and audio transcriptions. Filter by application name, window title, browser URL, date range. Full-text keyword search (SQLite FTS5) under the hood. Returns screenshots and audio clips alongside text results.
### Timeline view
Visual timeline of your entire screen history. Scroll through your day like a DVR. Click any moment to see the full screenshot and extracted text. Play back audio from any time period.
### Plugin system (Pipes)
Pipes are scheduled AI agents defined as markdown files. Each pipe is a `pipe.md` with a prompt and schedule — screenpipe runs an AI coding agent (like pi or claude-code) that queries your screen data, calls APIs, writes files, and takes actions. Built-in pipes include:
- **meeting-summary**: Summarizes the meeting that just ended and patches the note back onto the meeting record
- **day-recap**: Today's accomplishments, key moments, and unfinished work
- **standup-update**: What you did, what's next, and any blockers
- **time-breakdown**: Where your time went, by app, project, and category
- **ai-prompt-journal**: Captures every prompt you send to AI tools, saved to Obsidian or local markdown
- **video-export**: Create a video of your recent screen activity
Developers can create pipes by writing a markdown file in `~/.screenpipe/pipes/`.
#### Pipe data permissions
Each pipe supports YAML frontmatter fields that give admins deterministic, OS-level control over what data AI agents can access:
- **App & window filtering**: `allow-apps`, `deny-apps`, `deny-windows` (glob patterns)
- **Content type control**: restrict to `ocr`, `audio`, `input`, or `accessibility`
- **Time & day restrictions**: e.g. `time-range: 09:00-18:00`, `days: Mon,Tue,Wed,Thu,Fri`
- **Endpoint gating**: `allow-raw-sql: false`, `allow-frames: false`
Enforced at three layers — skill gating (AI never learns denied endpoints), agent interception (blocked before execution), and server middleware (per-pipe cryptographic tokens). Not prompt-based. Deterministic.
### MCP server (Model Context Protocol)
screenpipe runs as an MCP server, allowing AI assistants to query your screen history:
- Works with Claude Desktop, Cursor, VS Code (Cline, Continue), and any MCP-compatible client
- AI assistants can search your screen history, get recent context, and access meeting transcriptions
- Zero configuration: `claude mcp add screenpipe -- npx -y screenpipe-mcp@latest`
### Developer API
Full REST API running on localhost (default port 3030). Endpoints for searching screen content, audio, frames. Raw SQL access to the underlying SQLite database. JavaScript/TypeScript SDK available.
## Privacy and security
- **100% local by default**: All data stored on your device in a local SQLite database. Nothing sent to external servers.
- **Source-available**: fully auditable codebase; free for personal use.
- **Local AI support**: Use Ollama or any local model — no data sent to any cloud.
- **No account required**: Core application works without any sign-up.
- **You own your data**: Export, delete, or back up at any time.
- **Optional encrypted sync**: End-to-end encrypted sync between devices (zero-knowledge encryption).
- **AI data permissions**: Per-pipe YAML-based access control — deterministic enforcement at the OS level, not prompt-based. Three enforcement layers prevent AI agents from accessing unauthorized data.
## How screenpipe compares to alternatives
| Feature | screenpipe | Rewind / Limitless | Microsoft Recall | Granola |
|---------|-----------|-------------------|-----------------|---------|
| Source-available | ✅ fully auditable | ❌ | ❌ | ❌ |
| Platforms | macOS, Windows, Linux | macOS, Windows | Windows only | macOS only |
| Data storage | 100% local | Cloud required | Local (Windows) | Cloud |
| Multi-monitor | ✅ All monitors | ❌ Active window only | ✅ | ❌ Meetings only |
| Audio transcription | ✅ Local Whisper | ✅ | ❌ | ✅ Cloud |
| Developer API | ✅ Full REST API + SDK | Limited | ❌ | ❌ |
| Plugin system | ✅ Pipes (AI agents) | ❌ | ❌ | ❌ |
| AI model choice | Any (local or cloud) | Proprietary | Microsoft AI | Proprietary |
| Team deployment | ✅ Central config, AI permissions | ❌ | ❌ | ❌ |
| Pricing | Free OSS core · app from $25/mo | Subscription | Bundled with Windows | Subscription |
## Pricing
The source is available and free for personal use (see [LICENSE.md](LICENSE.md)). The signed desktop app uses a subscription:
- **Standard**: $25/month. Local-first capture, search, and timeline, all on your device.
- **Pro**: $50/seat/month. Everything in Standard plus cloud sync, cloud AI, and integrations. Teams buy 5+ seats self-serve.
- **Enterprise**: $150/seat/month. Managed deployment, central config, shared pipes, per-pipe AI data permissions, admin dashboard, SSO/SAML, MDM ready (Intune / SCCM). Sales-led. See [screenpi.pe/team](https://screenpi.pe/team).
Existing lifetime licenses remain valid; new lifetime purchases are no longer sold.
## Integrations
- **AI coding assistants**: Cursor, Claude Code, Cline, Continue, OpenCode, Gemini CLI
- **AI chat assistants**: ChatGPT (via MCP), Claude Desktop (via MCP), any MCP-compatible client
- **Note-taking**: Obsidian, Notion
- **Local AI**: Ollama, any OpenAI-compatible model server
- **Automation**: Custom pipes (scheduled AI agents as markdown files)
## Teams & enterprise
screenpipe Teams lets organizations deploy AI agents across their team with full control over what AI can access. See [screenpi.pe/team](https://screenpi.pe/team).
- **Central config management**: Push capture settings (app filters, schedules, URL rules) to every device from an admin dashboard.
- **Shared pipes**: Deploy AI workflows (auto-standups, meeting-to-tickets, time tracking) team-wide.
- **Per-pipe AI data permissions**: YAML frontmatter controls what each pipe can access — apps, windows, content types, time ranges, endpoints. Enforced deterministically at the OS level via three layers (skill gating, agent interception, server middleware with per-pipe cryptographic tokens).
- **Privacy boundary**: Admins control what gets captured and what AI accesses. They never see the actual data — everything stays on each employee's device.
- **Override rules**: Employees can add stricter filters (e.g. also block personal email) but cannot weaken admin-set rules.
- **MDM ready**: Deploy via Intune, SCCM, Robopack, or any MDM solution.
- **Enterprise**: SSO/SAML, audit logs, SLA, SOC 2 / HIPAA compliance ready.
## Technical architecture
1. **Event-driven capture**: Listens for OS events (app switch, click, typing pause, scroll, clipboard). When something meaningful happens, captures a screenshot + accessibility tree together with the same timestamp. Falls back to OCR when accessibility data isn't available. Idle fallback captures periodically when nothing is happening.
2. **Audio processing**: Whisper (local) or Deepgram (cloud) for speech-to-text. Speaker identification and diarization.
3. **Storage**: Local SQLite with FTS5 full-text search. Screenshots saved as JPEGs on disk (~300 MB/8hr vs ~2 GB with continuous recording).
4. **API layer**: REST API on localhost:3030. Search, frames, audio, elements, health, pipe management.
5. **Plugin layer**: Pipes — scheduled AI agents as markdown files. Agent executes prompts with access to screenpipe API.
6. **UI layer**: Desktop app built with Tauri (Rust + TypeScript).
## API examples
Search screen content:
```
GET http://localhost:3030/search?q=meeting+notes&content_type=all&limit=10
```
Search audio transcriptions:
```
GET http://localhost:3030/search?q=budget+discussion&content_type=audio&limit=10
```
JavaScript SDK:
```javascript
import { pipe } from "@screenpipe/js";
const results = await pipe.queryScreenpipe({
q: "project deadline",
contentType: "all",
limit: 20,
startTime: new Date(Date.now() - 24 * 60 * 60 * 1000).toISOString(),
});
```
## Building from source
Check CONTRIBUTING.
Make sure to understand the main branch is moving fast and breaking things, if you're looking for a stable version check app releases https://github.com/screenpipe/screenpipe/releases and use the git commit accordingly (production app is behind paywall).
## Frequently asked questions
**Is screenpipe free?**
The source is available and free for personal, non-commercial use, so you can build and run screenpipe yourself for free (see [LICENSE.md](LICENSE.md)); commercial use of the source requires a license. The signed desktop app uses a subscription starting at $25/month; existing lifetime licenses remain valid.
**Does screenpipe send my data to the cloud?**
No. All data is stored locally by default. You can use fully local AI models via Ollama for complete privacy.
**How much disk space does it use?**
~5–10 GB per month. Event-driven capture only stores frames when something changes, dramatically reducing storage compared to continuous recording.
**Does it slow down my computer?**
Typical CPU usage is 5–10% on modern hardware. Event-driven capture only processes frames when something changes, and accessibility tree extraction is much lighter than OCR.
**Can I use it with ChatGPT/Claude/Cursor?**
Yes. screenpipe runs as an MCP server, allowing Claude Desktop, Cursor, and other AI assistants to directly query your screen history.
**Can it record multiple monitors?**
Yes. screenpipe captures all connected monitors simultaneously.
**How does text extraction work?**
screenpipe primarily uses the OS accessibility tree to get structured text (buttons, labels, text fields) — this is faster and more accurate than OCR. When accessibility data isn't available (remote desktops, games, some Linux apps), it falls back to OCR: Apple Vision on macOS, Windows native OCR, or Tesseract on Linux.
**Can I deploy screenpipe to my team?**
Yes. Screenpipe Teams provides central config management, shared AI pipes, and per-pipe data permissions. Admins control what gets captured and what AI can access — employees' actual data never leaves their devices. See [screenpi.pe/team](https://screenpi.pe/team).
**How do AI data permissions work?**
Each pipe supports YAML frontmatter fields (allow-apps, deny-apps, deny-windows, allow-content-types, time-range, days, allow-raw-sql, allow-frames) that deterministically control what data the AI agent can access. Enforcement happens at three OS-level layers — not by prompting the AI to behave. Even a compromised agent cannot access denied data.
## Company
Built by screenpipe (Mediar, Inc.). Founded 2024. Based in San Francisco, CA.
- Founder: Louis Beaumont (@louis030195)
- Twitter: @screenpipe
- Email: louis@screenpi.pe