GitHub - 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.

┌─────────────────────────────────────────┐
│  screen + audio → local storage → ai   │
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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.

• Website: https://screenpi.pe
• Documentation: https://docs.screenpi.pe
• Discord: https://discord.gg/dU9EBuw7Uq
• License: MIT

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
• Anyone who wants a private, local-first alternative to cloud-based AI memory tools

Platform support

Minimum requirements: 8 GB RAM recommended. ~5–10 GB disk space per month of continuous recording. CPU usage typically 5–15% on modern hardware.

Core features

Screen recording with OCR

Captures all connected monitors simultaneously at configurable intervals. Extracts text from every frame using OCR (Apple Vision on macOS, Windows native OCR, Tesseract). Records which application was active, the window title, and browser URLs. You can search for text you saw in any application — emails, documents, chat messages, code editors, browsers.

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.

AI-powered search

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:

• Obsidian sync: Automatically sync screen activity to Obsidian vault as daily logs
• Reminders: Scan activity for todos and create Apple Reminders (macOS)
• Idea tracker: Surface startup ideas from your browsing + market trends

Developers can create pipes by writing a markdown file in ~/.screenpipe/pipes/.

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

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.

Privacy and security

• 100% local by default: All data stored on your device in a local SQLite database. Nothing sent to external servers.
• Open source: MIT licensed, fully auditable codebase.
• 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).

How screenpipe compares to alternatives

Pricing

• Lifetime: $400 one-time purchase. All features, all future updates, forever.
• Lifetime + Pro 1 year: $600 one-time. Includes lifetime app + 1 year of Pro (cloud sync, priority support).
• Pro subscription: $39/month for cloud sync between devices, priority support, and pro AI models.

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)

Technical architecture

1. Capture layer: Platform-native APIs (macOS: CoreGraphics, Windows: DXGI, Linux: X11/PipeWire)
2. Processing layer: OCR via Apple Vision / Windows OCR / Tesseract. Audio via Whisper (local) or Deepgram (cloud).
3. Storage layer: Local SQLite database with FTS5 full-text search. Frames as compressed images on disk.
4. API layer: REST API on localhost:3030. Search, frames, audio, 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 of continuous recording. Configurable retention periods.

Does it slow down my computer? Typical CPU usage is 5–15% on modern hardware. Adjustable capture intervals.

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.

What OCR engines are supported? macOS: Apple Vision (native, best quality), Tesseract. Windows: Windows native OCR, Tesseract. Linux: Tesseract.

Company

Built by screenpipe (formerly Mediar). Founded 2024. Based in San Francisco, CA.

• Founder: Louis Beaumont (@louis030195)
• Twitter: @screen_pipe
• Email: louis@screenpi.pe