Screen View

A powerful Model Context Protocol (MCP) tool that enables AI assistants to capture and analyze screenshots using Claude Vision API. Take screenshots, analyze screen content, and get AI insights about your desktop interface.

- 📸 Instant full-screen screenshot capture
- 🔍 AI-powered scene analysis with Claude Vision
- 🤖 Seamless integration with MCP-compatible AI assistants
- 🛠️ Easy configuration and setup
- 🔄 Support for both stdio and SSE transports

- Capture and analyze screenshots of your desktop
- Analyze UI elements and layouts
- Debug visual issues with screen captures
- Get AI insights about screen content
- Document interface elements and layouts
- Screen recording and analysis
- Desktop automation with visual feedback

The most reliable way to install Screen View MCP is through npm:

# Install the latest version npm install -g screen-view-mcp # To ensure you get the exact latest version and avoid caching issues npm install -g screen-view-mcp@2.0.15 # Replace with latest version number

Then configure your AI client as shown in the "Manual Configuration" section below.

After installing via npm, configure your AI client:

- Windows:%APPDATA%/Claude/claude_desktop_config.json
- MacOS:~/Library/Application Support/Claude/claude_desktop_config.json

- Windows:%APPDATA%/Cursor/mcp.jsonor~/.cursor/mcp.json
- MacOS:~/Library/Application Support/Cursor/mcp.json

{ "mcpServers": { "screen-view-mcp": { "command": "npx", "args": [ "screen-view-mcp@2.0.15" // Specify exact version to avoid caching issues ], "transport": "stdio", "env": { "ANTHROPIC_API_KEY": "your-anthropic-api-key" } } } }

For clients that support SSE transport or for remote connection scenarios:

{ "mcpServers": { "screen-view-mcp": { "command": "npx", "args": [ "screen-view-mcp@2.0.15", "--sse", "--port", "8080", "--host", "localhost" ], "env": { "ANTHROPIC_API_KEY": "your-anthropic-api-key" } } } }

For connecting to a remote SSE server (running on another machine):

{ "mcpServers": { "screen-view-mcp": { "url": "http://your-server-ip:8080/sse", "transport": "sse", "env": { "ANTHROPIC_API_KEY": "your-anthropic-api-key" } } } }

Captures and analyzes the current screen content.

{ prompt?: string; // Custom prompt for analysis modelName?: string; // Claude model to use saveScreenshot?: boolean; // Save screenshot locally }

Can you analyze what's on my screen right now and describe the layout?

- No access to screen capture: Make sure your AI client has screen capture permissions
- API key errors: Verify your Anthropic API key is valid and properly set in the configuration
- MCP tool not found: Ensure the package is installed globally (npm list -g screen-view-mcp)
- Package version issues: Specify the exact version in your configuration to avoid caching problems
- Transport issues: Confirm that you're using the right transport mode for your client

- For Claude Desktop, use stdio transport (default)
- For clients supporting SSE, you can use the--sseflag

Here are the transport types supported by different clients:

If you see connection errors, make sure you're using the correct transport configuration for your client.

git clone https://github.com/yourusername/screen-view-mcp.git cd screen-view-mcp npm install

# Test with stdio transport (default) node dist/screen-capture-mcp.js --api-key=your-anthropic-api-key # Test with SSE transport node dist/screen-capture-mcp.js --sse --port 8080 --host localhost --api-key=your-anthropic-api-key

This project is configured for deployment on Smithery, which allows hosting the MCP server over WebSocket transport.

- Dockerfile (included in repository)
- smithery.yaml (included in repository)
- Anthropic API Key (required during configuration)
- Add the server to Smithery
- Access the Deployments tab
- Configure with your Anthropic API Key
- Deploy the server

- anthropicApiKey(required): Your Anthropic API key
- verbose(optional): Enable verbose logging (default: false)

- helloWorld: Simple test tool that echoes a message
- captureAndAnalyzeScreen: Captures a screenshot and analyzes it using Claude Vision

const response = await mcpClient.invoke("captureAndAnalyzeScreen", { prompt: "What's on my screen right now? Focus on the main content.", modelName: "claude-3-opus-20240229" }); console.log(response);

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