Screenpipe SDK · for builders
Screen capture as a library.
Embed Screenpipe's capture engine in Electron, Swift, Tauri, and Node apps. Cross-platform screen + audio + OCR + accessibility capture without burning 18 months on OS edge cases.
SDK surfaces
One capture engine, four integration paths.
The SDK ships framework-specific surfaces instead of making every app build its own bridge. Pick the host runtime and keep the capture lifecycle consistent across products. Each app surface has a runnable example and smoke check in the repo.
Electron SDK
main + preload helpers
Use @screenpipe/sdk/electron to keep native capture in the main process while exposing a context-isolated renderer API for permissions, start, stop, snapshot, status, and reveal.
const { registerScreenpipeIpc } = require("@screenpipe/sdk/electron");Swift SDK
Swift Package
Use ScreenpipeClient from a native macOS app with async/await, typed request models, JPEG snapshot decoding, and a testable transport layer.
import ScreenpipeTauri SDK
frontend client + Rust plugin
Use @screenpipe/sdk/tauri with the Rust plugin to bridge Tauri commands into the same local capture lifecycle as Electron and Swift.
import { createScreenpipeTauriClient } from "@screenpipe/sdk/tauri";Node SDK
native addon
Use Recorder directly for headless capture, eval harnesses, dataset generation, and custom desktop tooling.
import { Recorder } from "@screenpipe/sdk";Building screen capture is a tar pit.
Different OS permissions. Audio routing. Accessibility APIs that change every year. DRM edge cases. macOS vs Windows vs Linux. Sleep/wake cycles eating CPU. PII.
We've been shipping it for 18 months across 200K+ installs. License the capture engine and build what actually differentiates your product.
What you get.
Drop-in capture engine
Bundle Screenpipe with your app. Use the Node core directly, or the Electron, Swift, and Tauri SDK layers for native desktop products.
Cross-platform, production-hardened
macOS (Apple Silicon + Intel), Windows x64 + ARM. Accessibility API for fast OCR-less capture. Audio routing handled. Battery-aware.
Local-first by design
Data never leaves the device unless you opt in. ChaCha20-Poly1305 encryption at rest. 27-pattern PII detection on-device, plus confidential-inference heavy-pass redaction using the OpenAI Privacy Filter model.
Commercial embedding license
Priority support, SLA, roadmap input, dedicated engineer. White-label options available under OEM.
Private beta · enterprise only
Confidential-inference PII redaction.
For fintech, healthcare, insurance, and other regulated verticals: we run OpenAI's Privacy Filter model inside a confidential-compute enclave (NVIDIA H200 TEE). Captured data is redacted before anyone — including us — can see it. Your buyers' CISOs, procurement, and compliance teams get the answer they're actually asking for: data never leaves an encrypted enclave.
View ScreenLeak PII benchmark8 PII categories detected
Names, addresses, emails, phone numbers, URLs, dates, account numbers (credit cards, bank accounts), secrets (passwords, API keys). F1 96% on PII-Masking-300k.
Open weights, confidential inference
OpenAI Privacy Filter (Apache 2.0, April 2026), hosted by us inside TEE-backed GPU enclaves. Attestation proofs available. Your data is processed without exposing it to us or the cloud provider.
Who embeds Screenpipe.
- 01Workflow and agent startups — capture what users do, find automation candidates, recommend agents. (e.g. Worktrace AI, building on Screenpipe in production.)
- 02Data companies — building computer-use datasets for labs. Every screen session becomes labeled trajectory data.
- 03Enterprise productivity tools — memory, meeting notes, CRM auto-capture, time tracking. Build the intelligence; skip the capture layer.
- 04Internal ops teams — embed in custom tools for workflow mapping, training data, knowledge capture across employee devices.
Want to embed Screenpipe?
30-minute call. Tell us about your product, we scope the embedding shape, and you leave with a proposal.
Book a call