# Supervision Draw

> Draw detections onto an image with Roboflow supervision's own annotators, over HTTP and MCP. Send a base64 image and detections (boxes in xyxy pixels, optional class_id, confidence, label, polygon) and get back the annotated image plus per-class counts. Annotators: box, round_box, box_corner, circle, dot, ellipse, triangle, label, color, mask, polygon, halo, background_overlay, blur, pixelate, percentage_bar, chained in order. A hosted alternative to installing Python and supervision just to render detection results.

An HTTP API at https://supervision-draw.saastemly.com, also an MCP server at https://supervision-draw.saastemly.com/mcp, paid per call: with x402 (USDC on Base; an unpaid call answers 402 Payment Required with the terms, which x402 clients pay automatically), or with prepaid credits or a monthly plan bought by card at https://supervision-draw.saastemly.com (send the API key as Authorization: Bearer <key>).

## Endpoints

- POST /v1/annotate ($0.003 per call; 3 free calls a day per caller with the header X-Free-Call: 1; MCP tool "annotate"): Annotate an image with detections using supervision's annotators (box, round_box, box_corner, circle, dot, ellipse, triangle, label, color, mask, polygon, halo, background_overlay, blur, pixelate, percentage_bar), applied in order. Input: base64 image up to 4 megapixels, up to 500 detections with xyxy pixel boxes and optional class_id, confidence, ASCII label, polygon. Returns the annotated image (base64 PNG or JPEG), size and counts per class.

## Examples

POST https://supervision-draw.saastemly.com/v1/annotate
```json
{
  "image": "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",
  "detections": [
    {
      "xyxy": [
        30,
        60,
        90,
        120
      ],
      "class_id": 0,
      "confidence": 0.94
    },
    {
      "xyxy": [
        140,
        40,
        180,
        115
      ],
      "class_id": 1,
      "confidence": 0.88
    },
    {
      "xyxy": [
        190,
        90,
        225,
        125
      ],
      "class_id": 2,
      "confidence": 0.71
    }
  ],
  "class_names": [
    "car",
    "person",
    "ball"
  ],
  "annotators": [
    {
      "type": "box",
      "thickness": 2
    },
    {
      "type": "label",
      "text_scale": 0.4,
      "text_padding": 4
    }
  ],
  "format": "jpeg",
  "quality": 85
}
```

## More

- [Pricing as JSON](https://supervision-draw.saastemly.com/v1/pricing)
- [OpenAPI description](https://supervision-draw.saastemly.com/openapi.json)
- [x402 discovery manifest](https://supervision-draw.saastemly.com/.well-known/x402)
- [MCP server](https://supervision-draw.saastemly.com/mcp): Streamable HTTP; add it to an MCP client with the header Authorization: Bearer <API key>
- [Home page](https://supervision-draw.saastemly.com/)