Peekaboo MCP

Peekaboo MCP: Lightning-fast macOS Screenshots & GUI Automation 🚀

Peekaboo Banner

🎉 NEW in v3: Complete GUI automation framework with AI Agent! Click, type, scroll, and automate any macOS application using natural language. Plus comprehensive menu bar extraction without clicking! See the GUI Automation section and AI Agent section for details.

Peekaboo is a powerful macOS utility for capturing screenshots, analyzing them with AI vision models, and now automating GUI interactions. It works both as a standalone CLI tool (recommended) and as an MCP server for AI assistants like Claude Desktop and Cursor.

🎯 Choose Your Path

🖥️ CLI Tool (Recommended for Most Users)

Perfect for:

Command-line workflows and automation
Shell scripts and CI/CD pipelines
Quick screenshots and AI analysis
System administration tasks

🤖 MCP Server (For AI Assistants)

Perfect for:

Claude Desktop integration
Cursor IDE workflows
AI agents that need visual context
Interactive AI debugging sessions

What is Peekaboo?

Peekaboo bridges the gap between visual content on your screen and AI understanding. It provides:

Lightning-fast screenshots of screens, applications, or specific windows
AI-powered image analysis using GPT-4.1 Vision, Claude, or local models
Complete GUI automation (v3) - Click, type, scroll, and interact with any macOS app
Natural language automation (v3) - AI agent that understands tasks like "Open TextEdit and write a poem"
Smart UI element detection - Automatically identifies buttons, text fields, links, and more with precise coordinate mapping
Menu bar extraction (v3) - Discover all menus and keyboard shortcuts without clicking or opening menus
Automatic session resolution - Commands intelligently use the most recent session (no manual tracking!)
Window and application management with smart fuzzy matching
Privacy-first operation with local AI options via Ollama
Non-intrusive capture without changing window focus
Automation scripting - Chain commands together for complex workflows

🏗️ Architecture

Peekaboo uses a modern service-based architecture:

PeekabooCore - Shared services for screen capture, UI automation, window management, and more
CLI - Command-line interface that uses PeekabooCore services directly
Mac App - Native macOS app with 100x+ performance improvement over CLI spawning
MCP Server - Model Context Protocol server for AI assistants

All components share the same core services, ensuring consistent behavior and optimal performance. See Service API Reference for detailed documentation.

🚀 Quick Start: CLI Tool

Installation

# Option 1: Homebrew (Recommended)
brew tap steipete/tap
brew install peekaboo

# Option 2: Direct Download
curl -L https://github.com/steipete/peekaboo/releases/latest/download/peekaboo-macos-universal.tar.gz | tar xz
sudo mv peekaboo-macos-universal/peekaboo /usr/local/bin/

# Option 3: npm (includes MCP server)
npm install -g @steipete/peekaboo-mcp

# Option 4: Build from source
git clone https://github.com/steipete/peekaboo.git
cd peekaboo
./scripts/build-cli-standalone.sh --install

Basic Usage

# Capture screenshots
peekaboo image --app Safari --path screenshot.png
peekaboo image --mode frontmost
peekaboo image --mode screen --screen-index 0

# List applications and windows
peekaboo list apps
peekaboo list windows --app "Visual Studio Code"

# Analyze images with AI
peekaboo analyze screenshot.png "What error is shown?"
peekaboo analyze ui.png "Find all buttons" --provider ollama

# GUI Automation (v3)
peekaboo see --app Safari               # Identify UI elements
peekaboo click "Submit"                 # Click button by text
peekaboo type "Hello world"             # Type at current focus
peekaboo scroll down --amount 5         # Scroll down 5 ticks

# AI Agent - Natural language automation
peekaboo "Open Safari and search for weather"
peekaboo agent "Fill out the contact form" --verbose
peekaboo hotkey cmd,c                   # Press Cmd+C

# AI Agent Automation (v3) 🤖
peekaboo "Open TextEdit and write Hello World"
peekaboo agent "Take a screenshot of Safari and email it"
peekaboo agent --verbose "Find all Finder windows and close them"

# Window Management (v3)
peekaboo window close --app Safari      # Close Safari window
peekaboo window minimize --app Finder   # Minimize Finder window
peekaboo window move --app TextEdit --x 100 --y 100
peekaboo window resize --app Terminal --width 800 --height 600
peekaboo window focus --app "Visual Studio Code"

# Menu Bar Interaction (v3)
peekaboo menu list --app Calculator     # List all menus and items
peekaboo menu list-all                  # List menus for frontmost app
peekaboo menu click --app Safari --item "New Window"
peekaboo menu click --app TextEdit --path "Format > Font > Bold"
peekaboo menu click-extra --title "WiFi" # Click system menu extras

# Configure settings
peekaboo config init                    # Create config file
peekaboo config edit                    # Edit in your editor
peekaboo config show --effective        # Show current settings

Debugging with Verbose Mode

All Peekaboo commands support the --verbose or -v flag for detailed logging:

# See what's happening under the hood
peekaboo image --app Safari --verbose
peekaboo see --app Terminal -v
peekaboo click --on B1 --verbose

# Verbose output includes:
# - Application search details
# - Window discovery information
# - UI element detection progress
# - Timing information
# - Session management operations

Verbose logs are written to stderr with timestamps:

[2025-01-06T08:05:23Z] VERBOSE: Searching for application: Safari
[2025-01-06T08:05:23Z] VERBOSE: Found exact bundle ID match: Safari
[2025-01-06T08:05:23Z] VERBOSE: Capturing window for app: Safari
[2025-01-06T08:05:23Z] VERBOSE: Found 3 windows for application

This is invaluable for:

Debugging automation scripts
Understanding why elements aren't found
Performance optimization
Learning Peekaboo's internals

Configuration

Peekaboo uses a unified configuration directory at ~/.peekaboo/ for better discoverability:

# Create default configuration
peekaboo config init

# Files created:
# ~/.peekaboo/config.json     - Main configuration (JSONC format)
# ~/.peekaboo/credentials     - API keys (chmod 600)

Managing API Keys Securely

# Set API key securely (stored in ~/.peekaboo/credentials)
peekaboo config set-credential OPENAI_API_KEY sk-...

# View current configuration (keys shown as ***SET***)
peekaboo config show --effective

Example Configuration

~/.peekaboo/config.json:

{
  // AI Provider Settings
  "aiProviders": {
    "providers": "openai/gpt-4.1,ollama/llava:latest",
    // NOTE: API keys should be in ~/.peekaboo/credentials
    "ollamaBaseUrl": "http://localhost:11434"
  },
  
  // Default Settings
  "defaults": {
    "savePath": "~/Desktop/Screenshots",
    "imageFormat": "png",
    "captureMode": "window",
    "captureFocus": "auto"
  },
  
  // Logging
  "logging": {
    "level": "info",
    "path": "~/.peekaboo/logs/peekaboo.log"
  }
}

~/.peekaboo/credentials (auto-created with proper permissions):

# Peekaboo credentials file
# This file contains sensitive API keys and should not be shared
OPENAI_API_KEY=sk-...
ANTHROPIC_API_KEY=sk-ant-...

Common Workflows

# Capture and analyze in one command
peekaboo image --app Safari --path /tmp/page.png && \
  peekaboo analyze /tmp/page.png "What's on this page?"

# Monitor active window changes
while true; do
  peekaboo image --mode frontmost --json-output | jq -r '.data.saved_files[0].window_title'
  sleep 5
done

# Batch analyze screenshots
for img in ~/Screenshots/*.png; do
  peekaboo analyze "$img" "Summarize this screenshot"
done

# Automated login workflow (v3 with automatic session resolution)
peekaboo see --app MyApp                # Creates new session
peekaboo click --on T1                  # Automatically uses session from 'see'
peekaboo type "user@example.com"        # Still using same session
peekaboo click --on T2                  # No need to specify --session
peekaboo type "password123"
peekaboo click "Sign In"
peekaboo sleep 2000                     # Wait 2 seconds

# Multiple app automation with explicit sessions
SESSION_A=$(peekaboo see --app Safari --json-output | jq -r '.data.session_id')
SESSION_B=$(peekaboo see --app Notes --json-output | jq -r '.data.session_id')
peekaboo click --on B1 --session $SESSION_A  # Click in Safari
peekaboo type "Hello" --session $SESSION_B   # Type in Notes

# Run automation script
peekaboo run login.peekaboo.json

🤖 MCP Server Setup

For AI assistants like Claude Desktop and Cursor, Peekaboo provides a Model Context Protocol (MCP) server.

For Claude Desktop

Edit your Claude Desktop configuration:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "peekaboo": {
      "command": "npx",
      "args": ["-y", "@steipete/peekaboo-mcp"],
      "env": {
        "PEEKABOO_AI_PROVIDERS": "openai/gpt-4.1,ollama/llava:latest",
        "OPENAI_API_KEY": "your-openai-api-key-here"
      }
    }
  }
}

For Claude Code

Run the following command:

claude mcp add-json peekaboo '{
  "command": "npx",
  "args": [
      "-y",
      "@steipete/peekaboo-mcp"
    ],
    "env": {
      "PEEKABOO_AI_PROVIDERS": "openai/gpt-4o,ollama/llava:latest",
      "OPENAI_API_KEY": "your-openai-api-key-here"
    }
}'

Alternatively, if you've already installed the server via Claude desktop, you can run:

claude mcp add-from-claude-desktop

For Cursor IDE

Add to your Cursor settings:

{
  "mcpServers": {
    "peekaboo": {
      "command": "npx",
      "args": ["-y", "@steipete/peekaboo-mcp"],
      "env": {
        "PEEKABOO_AI_PROVIDERS": "openai/gpt-4.1,ollama/llava:latest",
        "OPENAI_API_KEY": "your-openai-api-key-here"
      }
    }
  }
}

MCP Tools Available

Core Tools (v2)

image - Capture screenshots
list - List applications, windows, or check status
analyze - Analyze images with AI vision models

GUI Automation Tools (v3) 🎉

see - Capture screen and identify UI elements
click - Click on UI elements or coordinates
type - Type text into UI elements
scroll - Scroll content in any direction
hotkey - Press keyboard shortcuts
swipe - Perform swipe/drag gestures
run - Execute automation scripts
sleep - Pause execution
clean - Clean up session cache
window - Manipulate application windows (close, minimize, maximize, move, resize, focus)

🚀 GUI Automation with Peekaboo v3

Peekaboo v3 introduces powerful GUI automation capabilities, transforming it from a screenshot tool into a complete UI automation framework for macOS. This enables AI assistants to interact with any application through natural language commands.

How It Works

The v3 automation system uses a see-then-interact workflow:

See - Capture the screen and identify UI elements
Interact - Click, type, scroll, or perform other actions
Verify - Capture again to confirm the action succeeded

🎯 The `see` Tool - UI Element Discovery

The see tool is the foundation of GUI automation. It captures a screenshot and identifies all interactive UI elements, assigning them unique Peekaboo IDs.

// Example: See what's on screen
await see({ app_target: "Safari" })

// Returns:
{
  screenshot_path: "/tmp/peekaboo_123.png",
  session_id: "session_456",
  elements: {
    buttons: [
      { id: "B1", label: "Submit", bounds: { x: 100, y: 200, width: 80, height: 30 } },
      { id: "B2", label: "Cancel", bounds: { x: 200, y: 200, width: 80, height: 30 } }
    ],
    text_fields: [
      { id: "T1", label: "Email", value: "", bounds: { x: 100, y: 100, width: 200, height: 30 } },
      { id: "T2", label: "Password", value: "", bounds: { x: 100, y: 150, width: 200, height: 30 } }
    ],
    links: [
      { id: "L1", label: "Forgot password?", bounds: { x: 100, y: 250, width: 120, height: 20 } }
    ],
    // ... other elements
  }
}

Element ID Format

B1, B2... - Buttons
T1, T2... - Text fields/areas
L1, L2... - Links
G1, G2... - Groups/containers
I1, I2... - Images
S1, S2... - Sliders
C1, C2... - Checkboxes/toggles
M1, M2... - Menu items

🖱️ The `click` Tool

Click on UI elements using various targeting methods:

// Click by element ID from see command
await click({ on: "B1" })

// Click by query (searches button labels)
await click({ query: "Submit" })

// Click by coordinates
await click({ coords: "450,300" })

// Double-click
await click({ on: "I1", double: true })

// Right-click
await click({ query: "File", right: true })

// With custom wait timeout
await click({ query: "Save", wait_for: 10000 })

⌨️ The `type` Tool

Type text with support for special keys:

// Type into a specific field
await type({ text: "user@example.com", on: "T1" })

// Type at current focus
await type({ text: "Hello world" })

// Clear existing text first
await type({ text: "New text", on: "T2", clear: true })

// Use special keys
await type({ text: "Select all{cmd+a}Copy{cmd+c}" })
await type({ text: "Line 1{return}Line 2{tab}Indented" })

// Adjust typing speed
await type({ text: "Slow typing", delay: 100 })

Supported Special Keys

{return} or {enter} - Return/Enter key
{tab} - Tab key
{escape} or {esc} - Escape key
{delete} or {backspace} - Delete key
{space} - Space key
{cmd+a}, {cmd+c}, etc. - Command combinations
{arrow_up}, {arrow_down}, {arrow_left}, {arrow_right} - Arrow keys
{f1} through {f12} - Function keys

📜 The `scroll` Tool

Scroll content in any direction:

// Scroll down 3 ticks (default)
await scroll({ direction: "down" })

// Scroll up 5 ticks
await scroll({ direction: "up", amount: 5 })

// Scroll on a specific element
await scroll({ direction: "down", on: "G1", amount: 10 })

// Smooth scrolling
await scroll({ direction: "down", smooth: true })

// Horizontal scrolling
await scroll({ direction: "right", amount: 3 })

⌨️ The `hotkey` Tool

Press keyboard shortcuts:

// Common shortcuts
await hotkey({ keys: "cmd,c" })        // Copy
await hotkey({ keys: "cmd,v" })        // Paste
await hotkey({ keys: "cmd,tab" })      // Switch apps
await hotkey({ keys: "cmd,shift,t" })  // Reopen closed tab

// Function keys
await hotkey({ keys: "f11" })          // Full screen

// Custom hold duration
await hotkey({ keys: "cmd,space", hold_duration: 100 })

👆 The `swipe` Tool

Perform swipe or drag gestures:

// Basic swipe
await swipe({ from: "100,200", to: "300,200" })

// Slow drag
await swipe({ from: "50,50", to: "200,200", duration: 2000 })

// Precise movement with more steps
await swipe({ from: "0,0", to: "100,100", steps: 50 })

📝 The `run` Tool - Automation Scripts

Execute complex automation workflows from JSON script files:

// Run a script
await run({ script_path: "/path/to/login.peekaboo.json" })

// Continue on error
await run({ script_path: "test.peekaboo.json", stop_on_error: false })

Script Format (.peekaboo.json)

{
  "name": "Login to Website",
  "description": "Automated login workflow",
  "commands": [
    {
      "command": "see",
      "args": { "app_target": "Safari" },
      "comment": "Capture current state"
    },
    {
      "command": "click",
      "args": { "query": "Email" },
      "comment": "Click email field"
    },
    {
      "command": "type",
      "args": { "text": "user@example.com" }
    },
    {
      "command": "click",
      "args": { "query": "Password" }
    },
    {
      "command": "type",
      "args": { "text": "secure_password" }
    },
    {
      "command": "click",
      "args": { "query": "Sign In" }
    },
    {
      "command": "sleep",
      "args": { "duration": 2000 },
      "comment": "Wait for login"
    }
  ]
}

🤖 AI Agent Automation

Peekaboo v3 introduces an AI-powered agent that can understand and execute complex automation tasks using natural language. The agent uses OpenAI's Chat Completions API with streaming support to break down your instructions into specific Peekaboo commands.

Setting Up the Agent

# Set your OpenAI API key
export OPENAI_API_KEY="your-api-key-here"

# Or save it securely in Peekaboo's config
peekaboo config set-credential OPENAI_API_KEY your-api-key-here

# Now you can use natural language automation!
peekaboo "Open Safari and search for weather"

Two Ways to Use the Agent

1. Direct Natural Language (Default)

When you provide a text argument without a subcommand, Peekaboo automatically uses the agent:

# These all invoke the agent directly
peekaboo "Click the Submit button"
peekaboo "Open TextEdit and write Hello"
peekaboo "Take a screenshot of Safari"

2. Explicit Agent Command

Use the agent subcommand for more control and options:

# With options and flags
peekaboo agent "Fill out the contact form" --verbose
peekaboo agent "Close all Finder windows" --dry-run
peekaboo agent "Install this app" --max-steps 30 --json-output

How the Agent Works

Understands Your Intent - The AI agent analyzes your natural language request
Plans the Steps - Breaks down the task into specific actions
Executes Commands - Uses Peekaboo's automation tools to perform each step
Verifies Results - Takes screenshots to confirm actions succeeded
Handles Errors - Can retry failed actions or adjust approach

Real-World Examples

# Web Automation
peekaboo "Go to github.com and search for peekaboo"
peekaboo "Click the first search result"
peekaboo "Star this repository"

# Document Creation
peekaboo "Open Pages and create a new blank document"
peekaboo "Type 'Meeting Agenda' as the title and make it bold"
peekaboo "Add bullet points for Introduction, Main Topics, and Action Items"

# File Management
peekaboo "Open Finder and navigate to Downloads"
peekaboo "Select all PDF files and move them to Documents"
peekaboo "Create a new folder called 'Archived PDFs'"

# Application Testing
peekaboo "Launch Calculator and calculate 42 * 17"
peekaboo "Take a screenshot of the result"
peekaboo "Clear the calculator and close it"

# System Tasks
peekaboo "Open System Settings and go to Display settings"
peekaboo "Change the display resolution to 1920x1080"
peekaboo "Take a screenshot to confirm the change"

Agent Options

--verbose - See the agent's reasoning and planning process
--dry-run - Preview what the agent would do without executing
--max-steps <n> - Limit the number of actions (default: 20)
--model <model> - Choose OpenAI model (default: gpt-4-turbo)
--json-output - Get structured JSON output
--resume - Resume the latest unfinished agent session
--resume <session-id> - Resume a specific session by ID

Agent Capabilities

The agent has access to all Peekaboo commands:

Visual Understanding - Can see and understand what's on screen
UI Interaction - Click buttons, fill forms, navigate menus
Text Entry - Type text, use keyboard shortcuts
Window Management - Open, close, minimize, arrange windows
Application Control - Launch apps, switch between them
File Operations - Save files, handle dialogs
Complex Workflows - Chain multiple actions together

Understanding Agent Execution

When you run an agent command, here's what happens behind the scenes:

# Your command:
peekaboo "Click the Submit button"

# Agent breaks it down into:
peekaboo see                    # Capture screen and identify elements
peekaboo click "Submit"         # Click the identified button

Example Workflow

# Complex multi-step task
peekaboo agent --verbose "Create a new document in Pages with the title 'Meeting Notes' and add today's date"

# Agent will execute commands like:
# 1. peekaboo see --app Pages              # Check if Pages is open
# 2. peekaboo app launch Pages             # Launch if needed
# 3. peekaboo sleep --duration 2000        # Wait for app to load
# 4. peekaboo click "Create Document"      # Click new document
# 5. peekaboo type "Meeting Notes"         # Enter title
# 6. peekaboo hotkey cmd+b                 # Make text bold
# 7. peekaboo hotkey return                # New line
# 8. peekaboo type "Date: $(date)"         # Add current date

Debugging Agent Actions

Use --verbose to see exactly what the agent is doing:

peekaboo agent --verbose "Find and click the login button"

# Output will show:
# [Agent] Analyzing request...
# [Agent] Planning steps:
#   1. Capture current screen
#   2. Identify login button
#   3. Click on the button
# [Agent] Executing: peekaboo see
# [Agent] Found elements: button "Login" at (834, 423)
# [Agent] Executing: peekaboo click "Login"
# [Agent] Action completed successfully

Tips for Best Results

Be Specific - "Click the blue Submit button" works better than "submit"
One Task at a Time - Break complex workflows into smaller tasks
Verify State - The agent works best when it can see the current screen
Use Verbose Mode - Add --verbose to understand what the agent is doing
Set Reasonable Limits - Use --max-steps to prevent runaway automation

Resuming Agent Sessions

The agent supports resuming interrupted or incomplete sessions, maintaining full conversation context:

# Start a complex task
peekaboo agent "Help me write a document about automation"
# Agent creates document, starts writing...
# <Interrupted by Ctrl+C or error>

# Resume the latest session with context
peekaboo agent --resume "Continue where we left off"

# Or resume a specific session
peekaboo agent --resume session_abc123 "Add a conclusion section"

# List available sessions
peekaboo agent list-sessions

# See session details
peekaboo agent show-session --latest
peekaboo agent show-session session_abc123

How Resume Works

Session Persistence - Each agent run creates a session with a unique ID
Thread Continuity - Uses OpenAI's thread persistence to maintain conversation history
Context Preservation - The AI remembers all previous interactions in the session
Smart Recovery - Can continue from any point, understanding what was already done

Resume Examples

# Scenario 1: Continue an interrupted task
peekaboo agent "Create a presentation about AI"
# <Interrupted after creating first slide>
peekaboo agent --resume "Add more slides about machine learning"

# Scenario 2: Iterative refinement
peekaboo agent "Fill out this form with test data"
# <Agent completes task>
peekaboo agent --resume "Actually, change the email to test@example.com"

# Scenario 3: Debugging automation
peekaboo agent --verbose "Login to the portal"
# <Login fails>
peekaboo agent --resume --verbose "Try clicking the other login button"

⏸️ The `sleep` Tool

Pause execution between actions:

// Sleep for 1 second
await sleep({ duration: 1000 })

// Sleep for 500ms
await sleep({ duration: 500 })

🪟 The `window` Tool

Comprehensive window manipulation for any application:

// Close window
await window({ action: "close", app_target: "Safari" })
await window({ action: "close", window_title: "Downloads" })

// Minimize/Maximize
await window({ action: "minimize", app_target: "Finder" })
await window({ action: "maximize", app_target: "Terminal" })

// Move window
await window({ action: "move", app_target: "TextEdit", x: 100, y: 100 })

// Resize window
await window({ action: "resize", app_target: "Notes", width: 800, height: 600 })

// Set exact bounds (move + resize)
await window({ action: "set_bounds", app_target: "Safari", x: 50, y: 50, width: 1200, height: 800 })

// Focus window
await window({ action: "focus", app_target: "Visual Studio Code" })
await window({ action: "focus", window_index: 0 })  // Focus first window

// List all windows
await window({ action: "list", app_target: "Finder" })

Window Actions

close - Close the window (animated if has close button)
minimize - Minimize to dock
maximize - Maximize/zoom window
move - Move to specific coordinates
resize - Change window dimensions
set_bounds - Set position and size in one operation
focus - Bring window to front and focus
list - Get information about all windows

Targeting Options

app_target - Target by application name (fuzzy matching supported)
window_title - Target by window title (substring matching)
window_index - Target by index (0-based, front to back order)

📋 The `menu` Tool

Interact with application menu bars and system menu extras:

// List all menus and items for an app
await menu({ app_target: "Calculator", subcommand: "list" })

// Click a simple menu item
await menu({ app_target: "Safari", item: "New Window" })

// Navigate nested menus with path
await menu({ app_target: "TextEdit", path: "Format > Font > Bold" })

// Click system menu extras (WiFi, Bluetooth, etc.)
await menu({ subcommand: "click-extra", title: "WiFi" })

list - List all menus and their items (including keyboard shortcuts)
list-all - List menus for the frontmost application
click - Click a menu item (default if not specified)
click-extra - Click system menu extras in the status bar

Key Features

Pure Accessibility - Extracts menu structure without clicking or opening menus
Full Hierarchy - Discovers all submenus and nested items
Keyboard Shortcuts - Shows all available keyboard shortcuts
Smart Discovery - AI agents can use list to discover available options

🧹 The `clean` Tool

Clean up session cache and temporary files:

// Clean all sessions
await clean({})

// Clean sessions older than 7 days
await clean({ older_than_days: 7 })

// Clean specific session
await clean({ session_id: "session_123" })

// Dry run to see what would be cleaned
await clean({ dry_run: true })

Session Management

Peekaboo v3 uses sessions to maintain UI state across commands:

Sessions are created automatically by the see tool
Each session stores screenshot data and element mappings
Sessions persist in ~/.peekaboo/session/<PID>/
Element IDs remain consistent within a session
Sessions are automatically cleaned up on process exit

Best Practices

Always start with see - Capture the current UI state before interacting
Use element IDs when possible - More reliable than coordinate clicking
Add delays for animations - Use sleep after actions that trigger animations
Verify actions - Call see again to confirm actions succeeded
Handle errors gracefully - Check if elements exist before interacting
Clean up sessions - Use the clean tool periodically

Example Workflows

// 1. See the login form
const { elements } = await see({ app_target: "MyApp" })

// 2. Fill in credentials
await click({ on: "T1" })  // Click email field
await type({ text: "user@example.com" })

await click({ on: "T2" })  // Click password field  
await type({ text: "password123" })

// 3. Submit
await click({ query: "Sign In" })

// 4. Wait and verify
await sleep({ duration: 2000 })
await see({ app_target: "MyApp" })  // Verify logged in

Web Search

// 1. Focus browser
await see({ app_target: "Safari" })

// 2. Open new tab
await hotkey({ keys: "cmd,t" })

// 3. Type search
await type({ text: "Peekaboo MCP automation" })
await type({ text: "{return}" })

// 4. Wait for results
await sleep({ duration: 3000 })

// 5. Click first result
await see({ app_target: "Safari" })
await click({ on: "L1" })

Form Filling

// 1. Capture form
const { elements } = await see({ app_target: "Forms" })

// 2. Fill each field
for (const field of elements.text_fields) {
  await click({ on: field.id })
  await type({ text: "Test data", clear: true })
}

// 3. Check all checkboxes
for (const checkbox of elements.checkboxes) {
  if (!checkbox.checked) {
    await click({ on: checkbox.id })
  }
}

// 4. Submit
await click({ query: "Submit" })

Troubleshooting

Elements not found - Ensure the UI is visible and not obscured
Clicks not working - Try increasing wait_for timeout
Wrong element clicked - Use specific element IDs instead of queries
Session errors - Run clean tool to clear corrupted sessions
Permissions denied - Grant Accessibility permission in System Settings

🔧 Configuration

Configuration Precedence

Settings follow this precedence (highest to lowest):

Command-line arguments
Environment variables
Credentials file (~/.peekaboo/credentials)
Configuration file (~/.peekaboo/config.json)
Built-in defaults

Available Options

Setting	Config File	Environment Variable	Description
AI Providers	`aiProviders.providers`	`PEEKABOO_AI_PROVIDERS`	Comma-separated list (e.g., "openai/gpt-4.1,ollama/llava")
OpenAI API Key	Use `credentials` file	`OPENAI_API_KEY`	Required for OpenAI provider
Anthropic API Key	Use `credentials` file	`ANTHROPIC_API_KEY`	For Claude Vision (coming soon)
Ollama URL	`aiProviders.ollamaBaseUrl`	`PEEKABOO_OLLAMA_BASE_URL`	Default: http://localhost:11434
Default Save Path	`defaults.savePath`	`PEEKABOO_DEFAULT_SAVE_PATH`	Where screenshots are saved (default: current directory)
Log Level	`logging.level`	`PEEKABOO_LOG_LEVEL`	trace, debug, info, warn, error, fatal
Log Path	`logging.path`	`PEEKABOO_LOG_FILE`	Log file location
CLI Binary Path	-	`PEEKABOO_CLI_PATH`	Override bundled Swift CLI path (advanced usage)

Environment Variable Details

API Key Storage Best Practices

For security, Peekaboo supports three methods for API key storage (in order of recommendation):

Environment Variables (Most secure for automation)
export OPENAI_API_KEY="sk-..."
Credentials File (Best for interactive use)
peekaboo config set-credential OPENAI_API_KEY sk-... # Stored in ~/.peekaboo/credentials with chmod 600
Config File (Not recommended - use credentials file instead)

AI Provider Configuration

PEEKABOO_AI_PROVIDERS: Comma-separated list of AI providers to use for image analysis
- Format: provider/model,provider/model
- Example: "openai/gpt-4.1,ollama/llava:latest"
- The first available provider will be used
- Default: "openai/gpt-4.1,ollama/llava:latest"
OPENAI_API_KEY: Your OpenAI API key for GPT-4.1 Vision
- Required when using the openai provider
- Get your key at: https://platform.openai.com/api-keys
ANTHROPIC_API_KEY: Your Anthropic API key for Claude Vision
- Will be required when Claude Vision support is added
- Currently not implemented
PEEKABOO_OLLAMA_BASE_URL: Base URL for your Ollama server
- Default: http://localhost:11434
- Use for custom Ollama installations or remote servers

Default Behavior

PEEKABOO_DEFAULT_SAVE_PATH: Default directory for saving screenshots
- Default: Current working directory
- Supports tilde expansion (e.g., ~/Desktop/Screenshots)
- Created automatically if it doesn't exist

Logging and Debugging

PEEKABOO_LOG_LEVEL: Control logging verbosity
- Options: trace, debug, info, warn, error, fatal
- Default: info
- Use debug or trace for troubleshooting
PEEKABOO_LOG_FILE: Custom log file location
- Default: /tmp/peekaboo-mcp.log (MCP server)
- For CLI, logs are written to stderr by default

Advanced Options

PEEKABOO_CLI_PATH: Override the bundled Swift CLI binary path
- Only needed if using a custom-built CLI binary
- Default: Uses the bundled binary

Using Environment Variables

Environment variables can be set in multiple ways:

# For a single command
PEEKABOO_AI_PROVIDERS="ollama/llava:latest" peekaboo analyze image.png "What is this?"

# Export for the current session
export OPENAI_API_KEY="sk-..."
export PEEKABOO_DEFAULT_SAVE_PATH="~/Desktop/Screenshots"

# Add to your shell profile (~/.zshrc or ~/.bash_profile)
echo 'export OPENAI_API_KEY="sk-..."' >> ~/.zshrc

🎨 Setting Up Local AI with Ollama

For privacy-focused local AI analysis:

# Install Ollama
brew install ollama
ollama serve

# Download vision models
ollama pull llava:latest       # Recommended
ollama pull qwen2-vl:7b        # Lighter alternative

# Configure Peekaboo
peekaboo config edit
# Set providers to: "ollama/llava:latest"

📋 Requirements

macOS 14.0+ (Sonoma or later)
Screen Recording Permission (required)
Accessibility Permission (optional, for window focus control)

Granting Permissions

Screen Recording (Required):
- System Settings → Privacy & Security → Screen & System Audio Recording
- Enable for Terminal, Claude Desktop, or your IDE
Accessibility (Optional):
- System Settings → Privacy & Security → Accessibility
- Enable for better window focus control

🏗️ Building from Source

Prerequisites

macOS 14.0+ (Sonoma or later)
Node.js 20.0+ and npm
Xcode Command Line Tools (xcode-select --install)
Swift 5.9+ (included with Xcode)

Build Commands

# Clone the repository
git clone https://github.com/steipete/peekaboo.git
cd peekaboo

# Install dependencies
npm install

# Build everything (CLI + MCP server)
npm run build:all

# Build options:
npm run build         # TypeScript only
npm run build:swift   # Swift CLI only (universal binary)
./scripts/build-cli-standalone.sh         # Quick CLI build
./scripts/build-cli-standalone.sh --install # Build and install to /usr/local/bin

Creating Release Binaries

# Run all pre-release checks and create release artifacts
./scripts/release-binaries.sh

# Skip checks (if you've already run them)
./scripts/release-binaries.sh --skip-checks

# Create GitHub release draft
./scripts/release-binaries.sh --create-github-release

# Full release with npm publish
./scripts/release-binaries.sh --create-github-release --publish-npm

The release script creates:

peekaboo-macos-universal.tar.gz - Standalone CLI binary (universal)
@steipete-peekaboo-mcp-{version}.tgz - npm package
checksums.txt - SHA256 checksums for verification

Debug Build Staleness Detection

For development, enable automatic staleness detection to ensure you're always using the latest built CLI version: git config peekaboo.check-build-staleness true. This is recommended when working with AI assistants that frequently modify source code, as it prevents using outdated binaries.

👻 Poltergeist - Swift CLI Auto-rebuild Watcher

Poltergeist is a helpful ghost that watches your Swift files and automatically rebuilds the CLI when they change. Perfect for development workflows!

Installation

First, install Watchman (required):

brew install watchman

Usage

Run these commands from the project root:

# Start the watcher
npm run poltergeist:start
# or the more thematic:
npm run poltergeist:haunt

# Check status
npm run poltergeist:status

# View activity logs
npm run poltergeist:logs

# Stop watching
npm run poltergeist:stop
# or the more thematic:
npm run poltergeist:rest

What It Does

Poltergeist monitors:

Core/PeekabooCore/**/*.swift
Core/AXorcist/**/*.swift
Apps/CLI/**/*.swift
All Package.swift and Package.resolved files

When changes are detected, it automatically:

Rebuilds the Swift CLI using npm run build:swift
Copies the binary to the project root for easy access
Logs all activity to .poltergeist.log

Features

👻 Smart Rebuilding - Only rebuilds when Swift files actually change
🔒 Single Instance - Prevents multiple concurrent builds
📝 Activity Logging - Track all rebuild activity with timestamps
⚡ Native Performance - Uses macOS FSEvents for minimal overhead
🎯 Persistent Watches - Survives terminal sessions

🧪 Testing

# Test CLI directly
peekaboo list server_status
peekaboo image --mode screen --path test.png
peekaboo analyze test.png "What is shown?"

# Test MCP server
npx @modelcontextprotocol/inspector npx -y @steipete/peekaboo-mcp

📚 Documentation

🐛 Troubleshooting

Issue	Solution
`Permission denied`	Grant Screen Recording permission in System Settings
`Window not found`	Try using fuzzy matching or list windows first
`AI analysis failed`	Check API keys and provider configuration
`Command not found`	Ensure Peekaboo is in your PATH or use full path

Enable debug logging for more details:

export PEEKABOO_LOG_LEVEL=debug
peekaboo list server_status

For step-by-step debugging, use the verbose flag:

peekaboo image --app Safari --verbose 2>&1 | less

🤝 Contributing

Contributions are welcome! Please:

Fork the repository
Create a feature branch
Commit your changes
Push to the branch
Open a Pull Request

📝 License

MIT License - see LICENSE file for details.

👤 Author

Created by Peter Steinberger - @steipete

🙏 Acknowledgments

Apple's ScreenCaptureKit for blazing-fast captures
The MCP team for the Model Context Protocol
The Swift and TypeScript communities

Note: This is Peekaboo v3.0, which introduces GUI automation and AI agent capabilities. Configuration has moved from ~/.config/peekaboo/ to ~/.peekaboo/ for better discoverability. Migration happens automatically on first run. For full upgrade details, see the CHANGELOG.

Install Server

HTTP connection URL

security – no known vulnerabilities

license - permissive license

quality - confirmed to work

How are these scores calculated?

local-only server

The server can only run on the client's local machine because it depends on local resources.

Tools

A macOS utility that captures screenshots and analyzes them with AI vision, enabling AI assistants to see and interpret what's on your screen.

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Appeared in Searches

Desktop tools for showing pop-up windows during debugging

Peekaboo MCP: Lightning-fast macOS Screenshots & GUI Automation 🚀

🎯 Choose Your Path

🖥️ CLI Tool (Recommended for Most Users)

🤖 MCP Server (For AI Assistants)

What is Peekaboo?

🏗️ Architecture

🚀 Quick Start: CLI Tool

Installation

Basic Usage

Debugging with Verbose Mode

Configuration

Managing API Keys Securely

Example Configuration

Common Workflows

🤖 MCP Server Setup

For Claude Desktop

For Claude Code

For Cursor IDE

MCP Tools Available

Core Tools (v2)

GUI Automation Tools (v3) 🎉

🚀 GUI Automation with Peekaboo v3

How It Works

🎯 The see Tool - UI Element Discovery

Element ID Format

🖱️ The click Tool

⌨️ The type Tool

Supported Special Keys

📜 The scroll Tool

⌨️ The hotkey Tool

👆 The swipe Tool

📝 The run Tool - Automation Scripts

Script Format (.peekaboo.json)

🤖 AI Agent Automation

Setting Up the Agent

Two Ways to Use the Agent

1. Direct Natural Language (Default)

2. Explicit Agent Command

How the Agent Works

Real-World Examples

Agent Options

Agent Capabilities

Understanding Agent Execution

Example Workflow

Debugging Agent Actions

Tips for Best Results

Resuming Agent Sessions

How Resume Works

Resume Examples

⏸️ The sleep Tool

🪟 The window Tool

Window Actions

Targeting Options

📋 The menu Tool

Menu Subcommands

Key Features

🧹 The clean Tool

Session Management

Best Practices

Example Workflows

Login Automation

Web Search

Form Filling

Troubleshooting

🔧 Configuration

Configuration Precedence

Available Options

Environment Variable Details

API Key Storage Best Practices

AI Provider Configuration

Default Behavior

Logging and Debugging

Advanced Options

Using Environment Variables

🎨 Setting Up Local AI with Ollama

📋 Requirements

Granting Permissions

🏗️ Building from Source

Prerequisites

Build Commands

🎯 The `see` Tool - UI Element Discovery

🖱️ The `click` Tool

⌨️ The `type` Tool

📜 The `scroll` Tool

⌨️ The `hotkey` Tool

👆 The `swipe` Tool

📝 The `run` Tool - Automation Scripts

⏸️ The `sleep` Tool

🪟 The `window` Tool

📋 The `menu` Tool

🧹 The `clean` Tool