Image Tools Server

image_tools_server (doc_processing_std_tools.image_tools, MCP name image-tools) gives an agent seven tools to crop, resize, zoom, rotate, annotate, convert and inspect images with Pillow. It needs Pillow, which the docs and screenshot extras both install.

from doc_processing_std_tools import image_tools_server

The editing tools write a new file and return its path; they do not show the image to the model. To let the model see the result, pass the path to read_image.

Tools

Tool	Key parameters	Returns
image_crop	path, left, top, right, bottom, output_path, frame=0	Path of the cropped image (default <name>_cropped.<ext>)
image_resize	path, width, height, output_path, frame=0	Path of the resized image (default <name>_resized.<ext>). Give one dimension to keep the aspect ratio, or both for an exact size
image_zoom	path, region={"left", "top", "width", "height"}, zoom_factor=2.0, output_path, frame=0	Path of the enlarged region (default <name>_zoomed.<ext>)
image_rotate	path, angle (degrees, counter-clockwise), output_path, frame=0	Path of the rotated image (default <name>_rotated.<ext>); the canvas grows to fit
image_annotate	path, annotations (a JSON list), output_path, frame=0	Path of the annotated image (default <name>_annotated.<ext>)
image_convert	path, format (png, jpeg, webp, bmp, tiff), output_path, frame=0	Path of the converted image (default: same name with the new extension — .jpg for JPEG, .tif for TIFF)
image_get_info	path	JSON: width, height, format, mode, n_frames, is_animated, file_size_bytes, file_size_human

Annotation objects for image_annotate:

[
  {"type": "rectangle", "x": 40, "y": 60, "width": 200, "height": 80, "color": "red"},
  {"type": "text", "x": 40, "y": 30, "text": "Total", "font_size": 24, "color": "red"},
  {"type": "circle", "cx": 300, "cy": 200, "radius": 25, "color": "blue"},
  {"type": "arrow", "x1": 10, "y1": 10, "x2": 120, "y2": 90, "color": "green"}
]

How images are handled

• Orientation. Images are opened with their EXIF orientation applied, so coordinates match what a viewer shows. image_get_info reports the corrected dimensions.
• Quality and metadata. Saving keeps the ICC colour profile, EXIF data and DPI where the format allows. JPEG is written at quality 95 without chroma subsampling, WebP at quality 95.
• Format. The output format follows the output file's extension. Only image_convert changes the format. Converting to JPEG flattens transparency onto a white background.
• Multi-frame images. For an animated GIF or a multi-page TIFF, frame picks the frame (0-based); an out-of-range frame is an error.
• Size cap. Images above about 256 million pixels are refused as likely decompression bombs.

Environment variables

Variable	Default	Effect here
DPTTOOLS_MAX_FILE_SIZE_MB	50	Every tool refuses input files larger than this

Examples

Tool calls are written as Python calls; the model sends the same arguments as JSON.

image_get_info(path="scan.jpg")
image_zoom(path="scan.jpg", region={"left": 800, "top": 1200, "width": 400, "height": 200}, zoom_factor=3)
image_resize(path="photo.png", width=1200, output_path="photo_small.png")

Pitfalls

• The default output path sits next to the input and is overwritten if it exists. Pass output_path to choose the location. image_convert to the format the file already has, without an output_path, writes over the input itself.
• Coordinates are in pixels of the corrected image. Call image_get_info first to learn the dimensions; image_crop takes the box's right and bottom edges, while image_zoom takes a width and height.
• Edits do not reach the model by themselves. Follow an edit with read_image on the returned path when the model needs to see it. Zooming into a region first is a cheap way to let the model read small print.
• These tools do not scale for the model. They write files at the size you ask for. When the model looks at a result through read_image, that tool scales it to the model-safe limits (Images).