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mcp-image-extractor

一种模型上下文协议服务器,可以从URL或base64数据中提取图像,并将它们转换为适合LLM分析的格式,从而让AI模型能够处理和理解视觉内容。

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README

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
Image Extractor MCP server

How it looks in Cursor:

image

Suitable cases:

  • analyze playwright test results: screenshots

Installation

Recommended: Using npx in mcp.json (Easiest)

The recommended way to install this MCP server is using npx directly in your .cursor/mcp.json file:

{
  "mcpServers": {
    "image-extractor": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-image-extractor"
      ]
    }
  }
}

This approach:

  • Automatically installs the latest version
  • Does not require global installation
  • Works reliably across different environments

Alternative: Local Path Installation

If you prefer to use a local installation of the package, you can clone the repository and point to the built files:

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

Manual Installation

# 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.

Then configure in .cursor/mcp.json:

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

Troubleshooting for Cursor Users: If you see "Failed to create client" error, try the local path installation method above or ensure you're using the correct path to the executable.

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

help

Runtime guide

cloud

Hosted runtime

Hosted servers run from a provider-managed environment. You usually connect the MCP client to the hosted endpoint or follow the provider's authorization flow, without keeping a local process alive

  1. Open provider connection page
  2. Authorize or copy endpoint
  3. Connect from your MCP client
terminal

Local runtime / other methods

Local servers run on your own machine or infrastructure. You normally copy the server_config into your MCP client, install the required package, and provide env variables from env_schema when needed

  1. Copy server_config
  2. Install required package
  3. Fill env variables and restart client