mcp-image-tools
# mcp-image-tools
MCP server providing image analysis tools for AI agents. Metadata inspection only -- no image processing or manipulation.
## Tools
### image_metadata
Read image metadata from a URL using HTTP headers. Returns content-type, file size, last-modified, etag, and cache info without downloading the full image.
### find_favicons
Find all favicons for any website. Checks `/favicon.ico`, parses HTML `<link>` tags, and inspects `manifest.json`. Returns all discovered favicons with sizes and types.
### extract_og_image
Extract Open Graph image, Twitter card image, and Apple touch icon from any URL. Useful for generating link previews.
### generate_placeholder
Generate placeholder image URLs via the placehold.co API. Supports custom dimensions, colors, text, format, and font. Returns the URL plus ready-to-use HTML and Markdown markup. Can generate multiple sizes at once.
### responsive_images
Generate `srcset` and `<picture>` element HTML for responsive images. Given a base image URL, produces multiple size variants with proper markup for responsive design, including multi-format `<source>` elements.
## Setup
```bash
npm install
npm run build
```
## Usage with Claude Desktop
Add to your Claude Desktop config:
```json
{
"mcpServers": {
"image-tools": {
"command": "node",
"args": ["path/to/mcp-image-tools/dist/index.js"]
}
}
}
```
## License
MIT
TDQS
Scored across 5 tools
Each tool targets a distinct image-related task: reading HTTP headers, finding favicons, extracting social media images, generating responsive markup, and creating placeholders. No two tools could be confused for one another.
Tool names are a mix of verb-initial names (find_favicons, extract_og_image, generate_placeholder) and noun-phrase names (image_metadata, responsive_images). The lack of a consistent verb_noun pattern makes the set feel less predictable.
The server has 5 focused tools, which is well within the ideal range for a single-purpose utility server. Each tool earns its place without bloat.
The tools comprehensively cover common web image workflows: inspecting, discovering, generating, and integrating images. A minor gap is the lack of image transformation (e.g., resizing) but this is not clearly in scope.