Image Extractor
БесплатноНе проверенMCP server which allow LLM in agent mode to analyze image whenever it needs
Описание
MCP server which allow LLM in agent mode to analyze image whenever it needs
README
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:
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 datamime_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
Установка Image Extractor
У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.
▸ github.com/ifmelate/mcp-image-extractorFAQ
Image Extractor MCP бесплатный?
Да, Image Extractor MCP бесплатный — установка в пару кликов через Unyly без оплаты.
Нужен ли API-ключ для Image Extractor?
Нет, Image Extractor работает без API-ключей и переменных окружения.
Image Extractor — hosted или self-hosted?
Self-hosted: сервер запускается локально на твоей машине командой из раздела установки.
Как установить Image Extractor в Claude Desktop, Claude Code или Cursor?
Открой Image Extractor на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.
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