Image Extractor: Lightning-Fast, Effortless Image Harvesting

MCP Image Extractor

MCP server for extracting and converting images to base64 for LLM analysis.

This MCP server provides tools for AI assistants to:

• Extract images from local files
• Extract images from URLs
• Process base64-encoded images

How it looks in Cursor:

Installation

Via Smithery (Recommended)

The easiest way to install and use this MCP server is via Smithery.

For Claude Desktop

1. Open your terminal and run:

npx @smithery/cli install @ifmelate/mcp-image-extractor --client claude

2. The server will be automatically configured and ready to use in Claude Desktop.

For Cursor or Other Clients

For Cursor or other MCP clients, you can install the server from Smithery directly:

1. Visit Smithery and go to the Image Extractor page
2. Click on the "Connect" button and follow the instructions to install

Manual Installation

Since this package is only available in the Smithery registry and not in npm, you need to install it directly from GitHub:

# Clone and install 
git clone https://github.com/ifmelate/mcp-image-extractor.git
cd mcp-image-extractor
npm install
npm run build
npm link

This will make the mcp-image-extractor command available globally.

Configuration

For Claude Desktop

After installing via Smithery, the server should be automatically configured. If you need to manually configure it, add the following to your Claude Desktop settings:

{
  "mcpServers": {
    "image-extractor": {
      "command": "npx",
      "args": ["--yes", "@smithery/mcp-image-extractor"]
    }
  }
}

Settings file location:

• macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
• Windows: %APPDATA%\Claude\claude_desktop_config.json

For VSCode with Cline Extension

Add this configuration to the Cline MCP settings:

{
  "mcpServers": {
    "image-extractor": {
      "command": "npx",
      "args": ["--yes", "@smithery/mcp-image-extractor"]
    }
  }
}

Settings file location:

• macOS: ~/Library/Application Support/Code/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json
• Windows: %APPDATA%\Code\User\globalStorage\saoudrizwan.claude-dev\settings\cline_mcp_settings.json

For Cursor

You can configure Cursor to use this MCP server in one of the following ways:

Option 1: Using Cursor MCP Settings UI

Add this configuration through Cursor's MCP Settings UI:

{
  "mcpServers": {
    "image-extractor": {
      "command": "npx",
      "args": ["--yes", "@smithery/mcp-image-extractor"],
      "disabled": false
    }
  }
}

Option 2: Using .cursor/mcp.json file

For local development or when working in a specific project, you can add a .cursor/mcp.json file in your project root:

{
  "mcpServers": {
    "image-extractor": {
      "command": "node",
      "args": ["/full/path/to/mcp-image-extractor/dist/index.js"],
      "disabled": false
    }
  }
}

Or, if you've installed via npm link:

{
  "mcpServers": {
    "image-extractor": {
      "command": "mcp-image-extractor",
      "disabled": false
    }
  }
}

Important Note for Cursor Users : If you see "Failed to create client" error, try these alternatives:

Option 1: Use direct GitHub installation

git clone https://github.com/ifmelate/mcp-image-extractor.git
cd mcp-image-extractor
npm install
npm run build
npm link

Then configure in .cursor/mcp.json:

{
  "mcpServers": {
    "image-extractor": {
      "command": "mcp-image-extractor",
      "disabled": false
    }
  }
}

Option 2: Clone and run locally

git clone https://github.com/ifmelate/mcp-image-extractor.git
cd mcp-image-extractor
npm install
npm run build

Then configure in .cursor/mcp.json:

{
  "mcpServers": {
    "image-extractor": {
      "command": "node",
      "args": ["/full/path/to/mcp-image-extractor/dist/index.js"],
      "disabled": false
    }
  }
}

Configuration Options

When connecting via Smithery UI, you can configure:

• port : The port number for the server (default: 8000)
• maxImageSize : Maximum image size in bytes (default: 10485760)
• allowedDomains : Comma-separated list of allowed domains for URL extraction (default: all domains allowed)

Available Tools

extract_image_from_file

Extracts an image from a local file and converts it to base64.

Parameters:

• file_path (required): Path to the local image file

Note: All images are automatically resized to optimal dimensions (max 512x512) for LLM analysis to limit the size of the base64 output and optimize context window usage.

extract_image_from_url

Extracts an image from a URL and converts it to base64.

Parameters:

• url (required): URL of the image to extract

Note: All images are automatically resized to optimal dimensions (max 512x512) for LLM analysis to limit the size of the base64 output and optimize context window usage.

extract_image_from_base64

Processes a base64-encoded image for LLM analysis.

Parameters:

• base64 (required): Base64-encoded image data
• mime_type (optional, default: "image/png"): MIME type of the image

Note: All images are automatically resized to optimal dimensions (max 512x512) for LLM analysis to limit the size of the base64 output and optimize context window usage.

Example Usage

Here's an example of how to use the tools from Claude:

Please extract the image from this local file: images/photo.jpg

Claude will automatically use the extract_image_from_file tool to load and analyze the image content.

Please extract the image from this URL: https://example.com/image.jpg

Claude will automatically use the extract_image_from_url tool to fetch and analyze the image content.

Docker

Build and run with Docker:

docker build -t mcp-image-extractor .
docker run -p 8000:8000 mcp-image-extractor

License

MIT