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

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

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[ screenpipe ]

AI memory for your screen

AI finally knows what you’re doing

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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   │
└─────────────────────────────────────────┘

install

download the desktop app — one-time purchase, all features, auto-updates

or run the CLI:

npx screenpipe@latest record

then

claude mcp add screenpipe -- npx -y screenpipe-mcp

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


docs · discord · x · youtube · reddit

Contributing

See CONTRIBUTING.md for guidelines, maintainers, and how to submit PRs. AI/vibe-coded PRs welcome!

Thanks to all contributors:

📖 LLM reference

About screenpipe

screenpipe is an open source application (MIT license) 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 open source 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 open source option.

Who screenpipe is for

Platform support

PlatformSupportInstallation
macOS (Apple Silicon)✅ Full supportNative.dmg installer
macOS (Intel)✅ Full supportNative.dmg installer
Windows 10/11✅ Full supportNative.exe installer
Linux✅ SupportedBuild 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 OpenAI Whisper running locally on your device. Speaker identification and diarization. Works with any audio source — Zoom, Google Meet, Teams, or any other application.

Natural language search across all OCR text and audio transcriptions. Filter by application name, window title, browser URL, date range. Semantic search using embeddings. 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:

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:

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:

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.

Apple Intelligence integration (macOS)

On supported Macs, screenpipe uses Apple Intelligence for on-device AI processing — daily summaries, action items, and reminders with zero cloud dependency and zero cost.

How screenpipe compares to alternatives

FeaturescreenpipeRewind / LimitlessMicrosoft RecallGranola
Open source✅ MIT license
PlatformsmacOS, Windows, LinuxmacOS, WindowsWindows onlymacOS only
Data storage100% localCloud requiredLocal (Windows)Cloud
Multi-monitor✅ All monitors❌ Active window only❌ Meetings only
Audio transcription✅ Local Whisper✅ Cloud
Developer API✅ Full REST API + SDKLimited
Plugin system✅ Pipes (AI agents)
AI model choiceAny (local or cloud)ProprietaryMicrosoft AIProprietary
Team deployment✅ Central config, AI permissions
PricingOne-time purchaseSubscriptionBundled with WindowsSubscription

Pricing

Integrations

Teams & enterprise

screenpipe Teams lets organizations deploy AI agents across their team with full control over what AI can access. See screenpi.pe/team.

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=ocr&limit=10

Search audio transcriptions:

GET http://localhost:3030/search?q=budget+discussion&content_type=audio&limit=10

JavaScript SDK:

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(),
});

Frequently asked questions

Is screenpipe free? The core engine is open source (MIT license). The desktop app is a one-time lifetime purchase ($400). No recurring subscription required for the core app.

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.

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.