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aamar-shahzad

MCP Screenshot Server

by aamar-shahzad
OverviewSchemaRelated ServersScoreDiscussions
Python
Hybrid

MCP Screenshot Server 📸

A powerful Model Context Protocol (MCP) server for capturing screenshots and annotating images with boxes, lines, arrows, circles, text, and highlights.

Python License MCP

Features

🎯 Smart Annotation (NEW!)

  • 🧠 Unified - One tool for all annotation types

  • 📍 Flexible Positioning - Named positions ("top-left", "center"), percentages ("50%,30%"), or pixels

  • ⚓ Anchor & Offset - Control which part of annotation aligns to position, with pixel-level fine-tuning

  • 🔄 Auto-Adjust - Annotations automatically stay within image bounds

  • ⚡ Batch Annotations - Apply multiple annotations in a single call

  • 🏷️ Quick Labeling - Label multiple regions with one command

  • 🎯 Pixel-Perfect Mode - precise_annotate for exact coordinate control

🤖 AI Vision Integration

  • Works great with Gemini, Claude, and other vision models for intelligent annotation placement

  • AI can analyze images and provide exact coordinates for annotations

  • Combine vision analysis with precise_annotate for pinpoint accuracy

Capture & Load

  • 📷 Screenshot Capture - Full screen, region, or window-specific captures

  • 📂 Load Images - Load existing image files for annotation

Annotations

  • 📦 Box Annotation - Draw rectangles with customizable colors and fill

  • ➡️ Arrow Annotation - Draw directional arrows with adjustable head sizes

  • 📏 Line Drawing - Simple line annotations

  • ⭕ Circle/Ellipse - Draw circles and ellipses

  • 📝 Text Overlay - Add text with custom fonts and backgrounds

  • 🔦 Highlight Regions - Semi-transparent highlight overlays

  • 🔢 Numbered Callouts - Auto-numbered callouts for step-by-step guides

  • 🖼️ Border Tool - Add borders around images

Editing

  • 🔲 Blur/Pixelate - Hide sensitive information (passwords, emails)

  • ✂️ Crop - Crop images to specific regions

  • 📐 Resize - Resize with scale or exact dimensions

  • 🔄 Rotate/Flip - Rotate 90/180/270 degrees, flip horizontal/vertical

  • 🌓 Brightness/Contrast - Adjust image appearance

  • 💧 Watermark - Add text watermarks

  • ↩️ Undo - Undo annotations (up to 10 levels)

Export

  • 💾 Save Images - Export to PNG, JPG, WebP, and more

  • ⚡ Quick Save - One-click save to Desktop/Downloads

  • 📋 Clipboard Support - Copy images directly to system clipboard

  • 👁️ Preview Integration - Open in macOS Preview.app for native editing

  • 🐳 Docker Ready - Run as a containerized service

Examples

Screenshots captured from the browser and annotated using the MCP Screenshot Server tools:

Basic Annotations

Box, arrow, text, highlight, and circle annotations:

Basic Annotations

Numbered Callouts

Step-by-step guides with numbered markers:

Numbered Callouts

Highlights & Regions

Highlight important sections and mark areas for blur:

Highlights

Pixel-Perfect Annotations

Using precise_annotate with exact coordinates:

Pixel Perfect

PII Redaction

Blur or redact sensitive information:

PII Redacted

Quick Start

Installation

# Using pip pip install mcp-screenshot-server # Using uv (recommended) uv add mcp-screenshot-server # From source git clone https://github.com/aamar-shahzad/mcp-screenshot-server.git cd mcp-screenshot-server pip install -e .

Running the Server

# stdio transport (default - for Cursor AI, Claude Desktop, etc.) mcp-screenshot-server # HTTP transport (for web clients) mcp-screenshot-server --transport streamable-http --port 8000 # SSE transport mcp-screenshot-server --transport sse --port 8000

Integration with Cursor AI

Method 1: Local Installation (Recommended)

  1. Install the package:

    pip install mcp-screenshot-server # or uv tool install mcp-screenshot-server

  2. Add to Cursor settings (~/.cursor/mcp.json or workspace .cursor/mcp.json):

    { "mcpServers": { "screenshot": { "command": "mcp-screenshot-server", "args": [] } } }

  3. Restart Cursor to load the MCP server.

Method 2: Using uvx (No Installation)

{ "mcpServers": { "screenshot": { "command": "uvx", "args": ["mcp-screenshot-server"] } } }

Method 3: Using Docker

  1. Build the Docker image:

    docker build -t mcp-screenshot-server .

  2. Add to Cursor settings:

    { "mcpServers": { "screenshot": { "command": "docker", "args": ["run", "-i", "--rm", "mcp-screenshot-server"] } } }

Method 4: HTTP Transport

  1. Start the server:

    mcp-screenshot-server --transport streamable-http --port 8000

  2. Add to Cursor settings:

    { "mcpServers": { "screenshot": { "url": "http://localhost:8000/mcp" } } }

Available Tools

🎯 Smart Annotation Tools (Recommended!)

These tools use flexible positioning and auto-adjustment for easier annotation:

Tool

Description

annotate

Unified annotation with smart positioning

precise_annotate

Pixel-perfect annotations at exact coords

batch_annotate

Apply multiple annotations in ONE call

label_regions

Quickly label multiple areas with one command

Position Formats:

  • Named: "top-left", "center", "bottom-right", "top-right-quarter", etc.

  • Percentage: "50%, 30%" (from top-left)

  • Pixels: "100px, 200px" (absolute coordinates)

Anchor Options (controls which part of annotation aligns to position):

  • "top-left", "top-center", "top-right"

  • "center-left", "center", "center-right"

  • "bottom-left", "bottom-center", "bottom-right"

Examples:

# Smart annotation with anchor and offset annotate(img, "box", "830px, 195px", width=140, height=55, anchor="top-left", offset_x=0, offset_y=0) # Pixel-perfect annotation (no transformations) precise_annotate(img, "box", x=830, y=195, width=140, height=55, color="blue") precise_annotate(img, "text", x=830, y=168, text="Code Button", font_size=24) precise_annotate(img, "arrow", x=100, y=200, x2=300, y2=200, color="red") # Multiple annotations in one call batch_annotate(img, '[{"type":"box","position":"top-left"},{"type":"text","position":"center","text":"Hello"}]') # Label multiple regions at once label_regions(img, '{"Header":"top-center","Sidebar":"center-left","Main":"center"}')

🤖 Using with AI Vision Models

For the most accurate annotations, combine with vision-capable AI models:

1. Take screenshot with browser/capture tool 2. AI (Gemini/Claude) analyzes image and identifies element coordinates 3. Use precise_annotate with exact coordinates from AI 4. Result: pixel-perfect annotations every time

Screenshot Capture

Tool

Description

capture_screenshot

Capture full screen, region, or window screenshots

load_image

Load an existing image file for annotation

Basic Annotation Tools (for pixel-precise control)

Tool

Description

precise_annotate

NEW! Pixel-perfect multi-type tool

add_box

Draw rectangles/boxes on images

add_line

Draw lines on images

add_arrow

Draw arrows on images

add_text

Add text annotations

add_circle

Draw circles/ellipses

add_highlight

Add semi-transparent highlight regions

add_numbered_callout

Add auto-numbered callouts (1, 2, 3...)

add_border

Add border around entire image

Editing Tools

Tool

Description

blur_region

Blur/pixelate sensitive areas

crop_image

Crop image to specific region

resize_image

Resize with scale or dimensions

rotate_image

Rotate 90, 180, or 270 degrees

flip_image

Flip horizontal or vertical

adjust_brightness

Adjust image brightness

adjust_contrast

Adjust image contrast

add_watermark

Add text watermark

undo

Undo last annotation (up to 10 levels)

get_undo_count

Check available undo operations

reset_callout_counter

Reset auto-numbering to 0

Image Management

Tool

Description

list_images

List all images in the current session

get_image

Get a specific image by ID

duplicate_image

Create a copy of an existing image

delete_image

Remove an image from the session

Export Tools

Tool

Description

save_image

Save image to disk (PNG, JPG, WebP, etc.)

quick_save

Quick save to Desktop/Downloads/Documents

copy_to_clipboard

Copy image to system clipboard

get_image_base64

Get image as base64-encoded string

open_in_preview

Open image in macOS Preview or default viewer

open_file_in_preview

Open any image file in Preview/default viewer

macOS Preview Integration

On macOS, you can use the open_in_preview tool to open images in the native Preview.app, which provides additional markup tools.

Preview's Native Tools:

  • ✏️ Sketch - Freehand drawing

  • ⬜ Shapes - Rectangles, circles, arrows, speech bubbles

  • 📝 Text - Add text boxes with custom fonts

  • ✍️ Signature - Add your saved signature

  • 🎨 Colors - Full color picker

  • 📏 Border - Adjust line thickness

This allows you to combine MCP annotations with Preview's native tools for more complex edits.

Usage Examples

Basic Screenshot and Annotation

# In Cursor AI, you can ask: # "Take a screenshot and add a red box around the error message" # The AI will use these tools: # 1. capture_screenshot() -> returns image_id # 2. add_box(image_id, x=100, y=200, width=300, height=50, color="red") # 3. save_image(image_id, path="~/Desktop/annotated.png")

Creating a Bug Report Screenshot

User: Take a screenshot of my screen and highlight the button at coordinates (500, 300) with a red circle, add an arrow pointing to it, and save it. AI uses: 1. capture_screenshot(mode="fullscreen") 2. add_circle(image_id, x=500, y=300, radius=40, color="red", line_width=3) 3. add_arrow(image_id, x1=400, y1=200, x2=480, y2=280, color="red") 4. add_text(image_id, x=350, y=180, text="Click here!", color="red") 5. save_image(image_id, path="~/Desktop/bug-report.png")

Annotating an Existing Image

User: Load the image at ~/Downloads/mockup.png and add numbered callouts AI uses: 1. load_image(path="~/Downloads/mockup.png") 2. add_circle(image_id, x=100, y=100, radius=20, color="blue", fill="blue") 3. add_text(image_id, x=92, y=88, text="1", color="white") 4. add_circle(image_id, x=300, y=200, radius=20, color="blue", fill="blue") 5. add_text(image_id, x=292, y=188, text="2", color="white") 6. save_image(image_id, path="~/Downloads/mockup-annotated.png")

Docker Usage

Build and Run

# Build the image docker build -t mcp-screenshot-server . # Run with stdio transport docker run -i --rm mcp-screenshot-server # Run with HTTP transport docker run -p 8000:8000 mcp-screenshot-server \ --transport streamable-http --port 8000 # Run with volume for saving screenshots docker run -p 8000:8000 -v $(pwd)/screenshots:/app/screenshots \ mcp-screenshot-server --transport streamable-http

Docker Compose

# Start HTTP server docker-compose up -d mcp-screenshot-server # Start stdio server docker-compose --profile stdio up -d mcp-screenshot-server-stdio

Configuration

Environment Variables

Variable

Description

Default

MCP_HOST

Host for HTTP transport

0.0.0.0

MCP_PORT

Port for HTTP transport

8000

Command Line Arguments

mcp-screenshot-server [OPTIONS] Options: --transport {stdio,streamable-http,sse} Transport to use (default: stdio) --host HOST Host for HTTP transports (default: 0.0.0.0) --port PORT Port for HTTP transports (default: 8000)

Platform Support

Platform

Screenshot

Clipboard

Notes

macOS

✅ Native screencapture

✅ AppleScript

Full support

Windows

✅ PIL ImageGrab

✅ PowerShell

Full support

Linux

✅ PIL/scrot

✅ xclip/wl-copy

Requires X11/Wayland

Docker

✅ With Xvfb

⚠️ Limited

Headless mode

Development

Setup Development Environment

# Clone the repository git clone https://github.com/aamar-shahzad/mcp-screenshot-server.git cd mcp-screenshot-server # Install with development dependencies pip install -e ".[dev]" # Run tests pytest # Run linting ruff check src/

Project Structure

mcp-screenshot-server/ ├── src/ │ └── mcp_screenshot_server/ │ ├── __init__.py │ └── server.py # Main MCP server implementation ├── tests/ ├── Dockerfile ├── docker-compose.yml ├── pyproject.toml ├── README.md └── LICENSE

Troubleshooting

macOS: "screencapture" requires screen recording permission

Go to System Preferences > Privacy & Security > Screen Recording and enable the terminal or IDE you're using.

Linux: Clipboard not working

Install clipboard tools:

# For X11 sudo apt install xclip # For Wayland sudo apt install wl-clipboard

Docker: Screenshots are blank

The Docker container runs in headless mode. For actual screen capture, you need to run the server natively on the host system.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

  1. Fork the repository

  2. Create your feature branch (git checkout -b feature/amazing-feature)

  3. Commit your changes (git commit -m 'Add amazing feature')

  4. Push to the branch (git push origin feature/amazing-feature)

  5. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

Install Server
A
security – no known vulnerabilities
A
license - permissive license
A
quality - confirmed to work

How are these scores calculated?

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