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Screenpipe provides local-first computer history for AI agents by continuously recording screens, audio, and app context on macOS, Windows, and Linux. It builds a timestamped, searchable history from on-screen text, accessibility data, screen images, and audio transcripts to give AI models context about daily work.
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Evidence-backed listing facts
Only known values with retained provenance are shown. Missing fields are omitted instead of being filled with guesses.
- Primary job Verified
- Personal productivity
Evidence: Record your screen continuously locally and provide context to your agents
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- Pricing Verified
- Freemium
Evidence: Free Start on one device $0
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- Interfaces Verified
- Desktop / CLI / API
Evidence: download the desktop app — all features, auto-updates or run the CLI: npx screenpipe record
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- Source availability Verified
- Source available
Evidence: macOS · Windows · Linux · source-available
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- MCP support Verified
- Native
Evidence: screenpipe runs as an MCP server, allowing AI assistants to query your screen history
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- API Verified
- Public API
Evidence: Full REST API running on localhost (default port 3030).
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Reviewed sources
These sources were reachable when the listing evidence was checked.
Listing checked
About Screenpipe
Screenpipe provides local-first computer history for AI agents by continuously recording screens, audio, and app context on macOS, Windows, and Linux. It builds a timestamped, searchable history from on-screen text, accessibility data, screen images, and audio transcripts to give AI models context about daily work.
Evidence: screenpipe builds a timestamped, searchable history from on-screen text, app and window context, screen images, system audio, and microphone audio you choose to capture. Use it to find…
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By default, capture, transcriptions, and the search index remain locally stored on the device in a SQLite database. Screenpipe exposes this history to AI agents, apps, and developers through a local REST API and an MCP server.
Evidence: By default, capture, transcripts, and the search index stay on your device. Data leaves only when a feature you enable needs it, for example cloud AI, cloud sync, an export, a connector, or…
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Capabilities
Combines accessibility context, screen frames with OCR fallback, and system/microphone audio transcription into a structured local timeline.
Evidence: Combine accessibility data, screen frames with OCR fallback, and audio transcripts when text events are not enough.
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Includes automated redacting for sensitive text and custom filters to exclude specific apps, windows, or browser URLs.
Evidence: Exclude apps, windows, and URLs, then redact sensitive fields on your device.
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Runs as a local MCP server and local REST API, allowing AI tools like Claude or Cursor to query history.
Evidence: screenpipe runs as an MCP server, allowing AI assistants to query your screen history
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Supports automated, scheduled AI agents called Pipes defined as markdown files with deterministic YAML access controls.
Evidence: 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
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Use cases
Generating automated meeting notes, summaries, and action items when a meeting finishes.
Evidence: When a meeting ends, write a summary + action items and push to your notes. Runs on-device.
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Finding lost or past information on your screen using natural language queries.
Evidence: Find anything you’ve seen or heard. Turn meetings and daily work into summaries, follow-ups, and automations, while keeping the raw history local by default.
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Who Screenpipe fits — and what to check
Decision guidance below is tied to the cited evidence. Treat observed third-party claims as leads, not product guarantees.
Best for
Knowledge workers, developers, and researchers seeking a local-first, auditable alternative to cloud-based AI memory and screen tools.
Evidence: Anyone who wants a private, local-first alternative to cloud-based AI memory tools
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Limitations to check
Always-on capture continuously uses CPU, battery, and storage resources, and cannot recover uncaptured timeline gaps.
Evidence: Any always-on capture uses CPU, battery, and disk. The load depends on your displays, capture quality, audio sources, and local transcription settings.
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If subscription lapses on Enterprise deployments, query layers over custom S3 buckets become unqueryable through Screenpipe software within an hour.
Evidence: So if your subscription lapses or we suspend your account, your own bucket becomes unqueryable through our software within about an hour.
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Method: ClawSites keeps discovery copy separate from publishable claims, retains a source excerpt, and displays the date each cited source was checked. Pricing and availability can still change after that date.
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