AI Face Landmarks

Detect facial landmarks (68 points) and return coordinates for each face

json· JSON resultOpen tool

Quick start

Call this tool from your code in three languages.

cURL

# 1) Request a presigned URL → returns { uploadUrl, storageKey }
curl -X POST 'https://api.elysiatools.com/api/upload/presign/ai-face-landmarks' \
  -H 'Content-Type: application/json' \
  -d '{"filename":"imageFile.ext","contentType":"application/octet-stream","size":12345}'

# 2) PUT the file bytes directly to the presigned uploadUrl
curl -X PUT '<presigned uploadUrl>' \
  --data-binary @/path/to/file.ext

# 3) Call the tool, passing the returned storageKey for each file field
curl -X POST 'https://api.elysiatools.com/en/api/tools/ai-face-landmarks' \
  -F 'imageFile=uploads/2026/01/01/your-tool-1700000000000-abc123.ext' \
  -F 'minConfidence=0.5' \
  -F 'maxResults=0'

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/ai-face-landmarks

Parameters

Name	Type	Required	Description
imageFile	fileupload required	Yes	—
minConfidence	number	No	—
maxResults	number	No	—

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

Response format

JSON result

JSON

{
  "key": {...},
  "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-ai-face-landmarks": {
      "name": "ai-face-landmarks",
      "description": "Detect facial landmarks (68 points) and return coordinates for each face",
      "baseUrl": "https://api.elysiatools.com/mcp/sse?toolId=ai-face-landmarks",
      "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": "ai-face-landmarks",
    "arguments": {
  "imageFile": "https://example.com/file.ext",
  "minConfidence": 0.5,
  "maxResults": 0
}
  }
}

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]