sam3_image_visual_inference – 1 MCP server offers this tool
What it usually takes
bboxes– in 1 of 1im– in 1 of 1point_labels– in 1 of 1points– in 1 of 1variant– in 1 of 1
No server marks it as only reading: treat it as able to change data.
From each publisher's own tool list. We never call a tool.
Servers
| Server | Inputs | Read-only? |
|---|---|---|
SAM3 co.huggingface.gf-john/sam3 Segment objects in a single image with SAM3 using visual prompts (bounding boxes and/or points); a drop-in match for SAM2's process_image. Provide at least one of bboxes or points. Each bounding box produces its own mask; all points together describe one object and produce a single mask. The return value is a JSON list of base64-encoded 1-bit-PNG mask strings, ordered as: one mask per bounding box (in the order the boxes were given), then, if points were provided, one final mask for the points prompt. Each string decodes to a binary segmentation mask at the input image resolution; decode it with PIL, e.g. numpy.array(Image.open(io.BytesIO(base64.b64decode(mask_b64)))) to get a 0/255 mask. Box pixel coordinates use (x0, y0) = top-left and (x1, y1) = bottom-right corners of the ORIGINAL input image (albumentations "pascal_voc" [x_min, y_min, x_max, y_max], absolute pixels); point coordinates (x, y) are absolute pixels in the same image. Coordinate formats are documented at https://albume | bboxes,im,point_labels,points,variant | Not stated |