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Glama
openclaw

Peekaboo MCP

by openclaw
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Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
OPENAI_API_KEYNoYour OpenAI API key for using OpenAI models for image analysis.
PEEKABOO_CLI_PATHNoOptional override for the Swift peekaboo CLI executable path.uses bundled CLI
PEEKABOO_LOG_FILENoPath to the server's log file. If the specified directory is not writable, falls back to the system temp directory.~/Library/Logs/peekaboo-mcp.log
PEEKABOO_LOG_LEVELNoLogging level (trace, debug, info, warn, error, fatal).info
PEEKABOO_CLI_TIMEOUTNoTimeout in milliseconds for Swift CLI operations. Prevents hanging processes.30000
PEEKABOO_AI_PROVIDERSNoJSON string defining AI providers for image analysis. Format: 'provider_name/model_identifier' using commas or semicolons as separators.
PEEKABOO_CONSOLE_LOGGINGNoBoolean ("true"/"false") for development console logs.false
PEEKABOO_OLLAMA_BASE_URLNoBase URL for the Ollama API server. Only needed if Ollama is running on a non-default address.http://localhost:11434
PEEKABOO_DEFAULT_SAVE_PATHNoDefault directory for saving captured images when no path is specified.System temp directory

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Server capabilities have not been inspected yet.

Tools

Functions exposed to the LLM to take actions

NameDescription
imageA

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

analyzeA

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

listA

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

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

A4.2/5.0

Scored across 3 tools

Disambiguation5/5

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.

Naming Consistency3/5

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.

Tool Count5/5

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.

Completeness4/5

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.

Maintenance

ActivityNo data
ResponsivenessWithin a week

Resources