Design

Image Edge Detection

Apply professional edge detection algorithms (Sobel, Prewitt, Laplacian, Canny) with adjustable thresholds and visualization options

file· File resultOpen tool

Quick start

Call this tool from your code in three languages.

cURL

# 1) Upload each file first → returns { filePath }
curl -X POST 'https://api.elysiatools.com/upload/image-edge-detect' \
  -F 'file=@/path/to/imageFile.ext'

# 2) Call the tool with the returned filePath values
curl -X POST 'https://api.elysiatools.com/en/api/tools/image-edge-detect' \
  -F 'imageFile=/path/to/file.ext' \
  -F 'detectionMethod=sobel' \
  -F 'threshold=50' \
  -F 'threshold2=100' \
  -F 'apertureSize=3' \
  -F 'outputMode=edges-only' \
  -F 'edgeColor=white' \
  -F 'showOriginal=false' \
  -F 'format=original' \
  -F 'quality=95'

API reference

Send a POST request with your inputs as JSON. File parameters require a separate upload first.

Endpoint

HTTP

POST https://api.elysiatools.com/en/api/tools/image-edge-detect

Parameters

Name	Type	Required	Description
imageFile	fileupload required	Yes	Upload image for edge detection
detectionMethod	select	No	—
threshold	number	No	Threshold for edge detection (0-255)
threshold2	number	No	High threshold for Canny detector (0-255)
apertureSize	number	No	Kernel aperture size (odd number, 3-15)
outputMode	select	No	—
edgeColor	color	No	Color for detected edges (hex or R,G,B)
showOriginal	checkbox	No	Display original image alongside edge detection results
format	select	No	—
quality	number	No	Output quality for lossy formats

File-type parameters must be uploaded first via POST /upload/image-edge-detect, then the returned filePath is passed to the corresponding file field.

Response format

File result

JSON

{
  "filePath": "/public/processing/randomid.ext",
  "fileName": "output.ext",
  "contentType": "application/octet-stream",
  "size": 1024,
  "metadata": {
    "key": "value"
  },
  "error": "Error message (optional)",
  "message": "Notification message (optional)"
}

MCP integration

Add this tool to your Model Context Protocol server so AI agents can list and call it.

Server configuration

Add this block to your MCP client configuration:

mcp.json

{
  "mcpServers": {
    "elysiatools-image-edge-detect": {
      "name": "image-edge-detect",
      "description": "Apply professional edge detection algorithms (Sobel, Prewitt, Laplacian, Canny) with adjustable thresholds and visualization options",
      "baseUrl": "https://api.elysiatools.com/mcp/sse?toolId=image-edge-detect",
      "command": "",
      "args": [],
      "env": {},
      "isActive": true,
      "type": "sse"
    }
  }
}

List available tools

After connecting to the SSE endpoint, list the exposed tools:

tools/list

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/list"
}

Call this tool

Invoke the tool by its id, passing arguments built from its parameters:

tools/call

{
  "jsonrpc": "2.0",
  "id": 2,
  "method": "tools/call",
  "params": {
    "name": "image-edge-detect",
    "arguments": {
  "imageFile": "https://example.com/file.ext",
  "detectionMethod": "sobel",
  "threshold": 50,
  "threshold2": 100,
  "apertureSize": 3,
  "outputMode": "edges-only",
  "edgeColor": "white",
  "showOriginal": false,
  "format": "original",
  "quality": 95
}
  }
}

Chain multiple tools in one session with a comma-separated toolId list, e.g. /mcp/sse?toolId=png-to-webp,jpg-to-webp,gif-to-webp (max 20).

File parameters accept a public file URL only (https://…). Local paths, data: URIs, and Base64 strings are not supported.

Questions or issues? Contact [email protected]