Peekaboo MCP provides macOS screen capture, AI image analysis, and system/window listing.
Capture entire screens, a specific display, the frontmost app, a named/PID app, or a specific app window; choose background/auto/foreground focus.
Save captures as PNG/JPG or return inline Base64 data, and optionally analyze the capture with an AI model using a question.
Analyze existing local images (.png/.jpg/.webp) with an AI model to answer questions, describe content, or extract text/OCR; optionally specify provider/model.
List running applications, open windows for an app with optional IDs, bounds, and off-screen status, or server status/version/AI providers.
Enables comprehensive screen capture capabilities on macOS, including capturing entire screens, specific application windows, or all windows of an app with various formatting options.
Enables local AI image analysis of screenshots through Ollama, supporting models like LLaVA and Qwen2-VL for vision tasks without sending data to the cloud.
Provides integration with OpenAI's vision models (like GPT-4o) for analyzing captured screenshots through the OpenAI API.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Peekaboo MCP take a screenshot of my current screen and describe what you see"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Peekaboo is a macOS CLI and menu-bar app for screen capture, accessibility inspection, and native UI automation. Use it directly, let its agent plan multi-step work, or expose the same toolset to MCP clients.
The released CLI and app require macOS 15 or later.
brew install openclaw/tap/peekabooThe npm package requires Node.js 22 or later and includes the CLI plus its MCP launcher.
npx -y @steipete/peekaboo --versionSee MCP setup to connect it to Codex, Claude Code, Cursor, or another MCP client.
Download the signed DMG from the latest GitHub release. The menu-bar app provides permission onboarding, visual feedback, and agent sessions; install the CLI separately when you also need peekaboo on PATH.
For source builds and alternative install details, see the installation guide.
Related MCP server: Screen View MCP
Check the permissions available to Peekaboo, then take a screenshot:
peekaboo permissions status
peekaboo see --no-elements --mode screen --path /tmp/peekaboo-screen.pngScreen capture requires Screen Recording permission. Accessibility permission enables UI inspection and control; the permissions guide covers setup and the additional permission used for synthetic input.
Inspect a running app to get a structured UI map with opaque element IDs:
peekaboo see --app Finder --jsonThat is the core loop: observe the current screen, choose an element from the result, and act on it.
Peekaboo 4.9.8 is a fix release. dialog file can now select a file in an Open panel, going through Go to Folder and checking the selection before it confirms, and it no longer types filenames into Search. Exact-window clicks and window focus keep working when another running app shares the target's name, see and window list find windows that an app exposes only through its focused or main window, window focus falls back to Accessibility when macOS declines activation, and MCP starts when another Peekaboo process owns the capture lane without a Bridge.
List Safari's windows, copy the intended window_id (12345 below), then keep the entire interaction pinned to
that exact window:
peekaboo window list --app Safari --json
peekaboo click "Address and search bar" --app Safari --window-id 12345
peekaboo type "github.com/openclaw/Peekaboo" --app Safari --window-id 12345
peekaboo press Return --app Safari --window-id 12345Targeted semantic and typed CLI input uses background delivery when Peekaboo can resolve the process, so the app does
not have to become frontmost. Raw CLI press chords can also stay background with an exact window selector. The CLI
also accepts a fresh exact non-dialog snapshot; that snapshot is required by background-only Agent/MCP policy.
App/PID-only and targetless chords require explicit foreground consent, as do window-selector-only Agent/MCP chords.
Prefer a semantic action such as menu click when one exists. See the
automation guide for element IDs, coordinates, snapshots, waits, and input behavior.
The agent combines the same observation and action tools into a natural-language run:
peekaboo agent "Open Safari, go to github.com, and search for Peekaboo" --allow-foregroundAgent runs need a configured model provider. See agent setup for providers and sessions, or MCP setup to expose Peekaboo's tools to another client.
Goal | Commands | Guide |
Observe the desktop |
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Interact with UI |
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Control macOS |
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Run workflows |
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Integrate with clients |
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Run peekaboo help <command> for live CLI help. The complete command index links to flags, examples, and troubleshooting for every command.
Peekaboo stores provider credentials and settings under ~/.peekaboo. Use peekaboo config to inspect or change them, and consult the configuration guide for profiles, environment variables, and custom providers. The provider reference covers hosted, compatible, and local model backends.
Shell completions for zsh, bash, and fish come from peekaboo completions; see the completion guide for persistent setup.
PeekabooWin — Windows-first rewrite of the Peekaboo automation loop (JavaScript + PowerShell) by @FelixKruger
PeekabooX — Linux-first rewrite of the Peekaboo automation loop (Rust + Python) by @nordbyte
Source builds require macOS 15 or later, Swift 6.2 or later, Node.js 22 or later, and the repository's submodules.
pnpm install --frozen-lockfile
pnpm run build:cli
pnpm run lint:docs
pnpm run test:safeMore build, signing, and test details live in docs/building.md.
MIT. See LICENSE.
Analyzes a pre-existing image file from the local filesystem using a configured AI model.
This tool is useful when an image already exists (e.g., previously captured, downloaded, or generated) and you need to understand its content, extract text, or answer specific questions about it.
Capabilities:
Image Understanding: Provide any question about the image (e.g., "What objects are in this picture?", "Describe the scene.", "Is there a red car?").
Text Extraction (OCR): Ask the AI to extract text from the image (e.g., "What text is visible in this screenshot?").
Flexible AI Configuration: Can use server-default AI providers/models or specify a particular one per call via 'provider_config'.
Example: If you have an image '/tmp/chart.png' showing a bar chart, you could ask: { "image_path": "/tmp/chart.png", "question": "Which category has the highest value in this bar chart?" } The AI will analyze the image and attempt to answer your question based on its visual content. Peekaboo MCP 1.1.0 using openai/gpt-4-vision, anthropic/claude-3-opus, google/gemini-pro-vision
Inputs: question (required), image_path, provider_config.
Captures macOS screen content and optionally analyzes it. Targets can be entire screen, specific app window, or all windows of an app (via app_target). Supports foreground/background capture. Output via file path or inline Base64 data (format: "data"). If a question is provided, image is analyzed by an AI model (auto-selected from PEEKABOO_AI_PROVIDERS). Window shadows/frames excluded. Peekaboo MCP 1.1.0 using openai/gpt-4-vision, anthropic/claude-3-opus, google/gemini-pro-vision
Inputs: format (required), path (required), app_target, capture_focus, +1 more.
Lists various system items on macOS, providing situational awareness.
Capabilities:
Running Applications: Get a list of all currently running applications (names and bundle IDs).
Application Windows: For a specific application (identified by name or bundle ID), list its open windows.
Details: Optionally include window IDs, bounds (position and size), and whether a window is off-screen.
Multi-window apps: Clearly lists each window of the target app.
Server Status: Provides information about the Peekaboo MCP server itself (version, configured AI providers).
Use Cases:
Agent needs to know if 'Photoshop' is running before attempting to automate it. { "item_type": "running_applications" } // Agent checks if 'Photoshop' is in the list.
Agent wants to find a specific 'Notes' window to capture. { "item_type": "application_windows", "app": "Notes", "include_window_details": ["ids", "bounds"] } The agent can then use the window title or ID with the 'image' tool. Peekaboo MCP 1.1.0 using openai/gpt-4-vision, anthropic/claude-3-opus, google/gemini-pro-vision
Inputs: include_window_details (required), item_type (required), app.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
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Scored across 3 tools
Each tool has a clearly distinct purpose with no overlap: 'analyze' processes existing image files, 'image' captures screen content, and 'list' provides system information. The boundaries are well-defined, making it easy for an agent to select the right tool for each task.
The naming is mixed: 'analyze' and 'list' are simple verbs, while 'image' is a noun, breaking a consistent pattern. However, the names are still readable and descriptive of their functions, though they lack a uniform verb_noun or other predictable convention.
With 3 tools, the count is well-scoped for a macOS screen capture and analysis server. Each tool serves a distinct, essential function (analysis, capture, and system listing), and there are no extraneous tools, making the set focused and efficient.
The tool set covers core workflows for screen capture and analysis on macOS, including listing apps/windows, capturing images, and analyzing them. A minor gap is the lack of tools for managing or deleting captured images, but agents can work around this using the provided tools effectively.
Capture screenshots, detect visual regressions between page versions, and analyze with AI.
Turn screen recordings into step-by-step guides, SOPs, tutorials and user docs with screenshots.
AI-designed App Store screenshot sets from your app's screens, uploaded to App Store Connect.
Memory for your AI: what you saw on screen, said in calls and worked on, searchable by agents.
