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Peekaboo is a macOS CLI and MCP server tool that lets AI agents capture screenshots and automate GUI interactions through natural language commands. It supports visual question answering via local or remote AI models and works with Claude, OpenAI, and Anthropic-compatible providers.
Key facts
Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.
| Field | Value |
|---|---|
| Repository | openclaw/Peekaboo |
| Owner | openclaw |
| Primary language | Swift |
| License | MIT — OSI-approved |
| Stars | 4.8k |
| Forks | 375 |
| Open issues | 8 |
| Latest release | v3.7.1 (2026-07-05) |
| Last updated | 2026-07-05 |
| Source | https://github.com/openclaw/Peekaboo |
What Peekaboo is
Written in Swift, Peekaboo provides pixel-accurate screen capture, accessibility-based UI automation (click, type, scroll, keyboard), menu/menubar discovery, and a native agent that chains commands. It runs as a standalone CLI, Homebrew app, or Node.js MCP server compatible with Claude, Codex, and Cursor.
Get the Peekaboo source
Clone the repository and explore it locally.
git clone https://github.com/openclaw/Peekaboo.gitcd Peekaboo# follow the project's README for install & configurationNeed it deployed, integrated, or customized instead? DEV.co ships production installs.
Best use cases
Implementation considerations
- Requires explicit Screen Recording and Accessibility OS permissions; plan user onboarding and IT approval cycles. Background input delivery optional via --foreground flag for apps rejecting process-targeted input.
- Snapshot-based state tracking; capture must precede element references. Plan for latency between `see` and `click` when UI changes rapidly.
- AI provider configuration via environment variables (PEEKABOO_AI_PROVIDERS) or config file; test model temperature/max-token clamping for each provider.
- Node 22+ required for MCP server; Swift 6.2 for CLI/app. Verify agent reliability in scripted workflows; natural language chains are non-deterministic.
- Multi-screen support confirmed but test drag/window operations across screens; coordinate space handling edge cases should be verified in target setup.
When to avoid it — and what to weigh
- Windows/Linux Primary Target — Peekaboo is macOS-only (requires macOS 15.0+/Sequoia). Not suitable for cross-platform automation or non-Apple workflows.
- No System Permissions Available — Requires Screen Recording and Accessibility permissions; not deployable in locked-down MDM or kiosk environments without permission grants.
- Headless Server Deployments — Designed for interactive machines with a display. Not intended for headless server automation or cloud-hosted agents that need macOS GUI access.
- Production SLAs Without Vendor Support — Open-source community project; no commercial support tier or guaranteed SLA. Risky for critical business workflows requiring vendor responsibility.
License & commercial use
Licensed under MIT (permissive open-source). Permits commercial use, modification, and redistribution provided the license and copyright notice are retained.
MIT license permits commercial use without restriction. However, this is a community-maintained open-source project with no vendor support agreement, warranty, or SLA. Commercial deployments should assess build/support strategy independently and not assume vendor liability or patches.
DEV.co evaluation signals
Editorial assessment — not user reviews. Directional, with an explicit confidence level.
| Signal | Assessment |
|---|---|
| Maintenance | Active |
| Documentation | Adequate |
| License clarity | Clear |
| Deployment complexity | Low |
| DEV.co fit | Good |
| Assessment confidence | High |
Requires Screen Recording and Accessibility permissions—powerful OS capabilities. Review threat model if automating sensitive data input or screen capture. Background input delivery defaults to process-targeted (safer); foreground input visible to system. No mention of audit logging, clipboard encryption, or secrets handling. Daemon/socket model with permission isolation noted but security audit not provided in data. Evaluate for compliance requirements (e.g., FedRAMP, SOC 2) if used in regulated contexts.
Alternatives to consider
PyAutoGUI / PyRobotFramework
Cross-platform GUI automation; less AI-native but more mature, wider OS support, larger community. Steeper learning curve for ML agent integration.
OCR + Coordinate-Based Tools (Sikuli, ImageMagick + xdotool)
Lower-level, language-agnostic; no AI integration built-in. More portable across Unix-like systems but requires more glue code and OCR plumbing.
Apple's native Automation scripting (AppleScript, Shortcuts)
First-party, no third-party dependency; excellent for simple macOS workflows. No AI/vision capability, steeper learning curve for complex logic, less suited to LLM-based agents.
Build on Peekaboo with DEV.co software developers
Evaluate Peekaboo's fit for your workflow: test the Homebrew install, review permission requirements, and explore MCP integration with Claude or Cursor. Start with non-critical automation tasks to assess reliability.
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Peekaboo FAQ
Does Peekaboo work on non-macOS?
Can I use Peekaboo without granting Screen Recording and Accessibility permissions?
What AI models are supported?
Is there a commercial support offering or SLA?
Build it with a software development company
From first prototype to production, DEV.co delivers custom software development around tools like Peekaboo. We staff experienced engineers for integrations, web development, and ongoing support across mcp servers and beyond.
Ready to automate macOS with AI?
Evaluate Peekaboo's fit for your workflow: test the Homebrew install, review permission requirements, and explore MCP integration with Claude or Cursor. Start with non-critical automation tasks to assess reliability.