Media

Batch Image Resize

Resize multiple images to specific dimensions with various resize options and batch processing

file· File 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/batch-resize' \
  -H 'Content-Type: application/json' \
  -d '{"filename":"imageFiles.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/batch-resize' \
  -F 'imageFiles=uploads/2026/01/01/your-tool-1700000000000-abc123.ext' \
  -F 'width=800' \
  -F 'height=600' \
  -F 'fit=cover' \
  -F 'position=center' \
  -F 'format=original' \
  -F 'quality=85' \
  -F 'preserveMetadata=false' \
  -F 'upscale=false' \
  -F 'kernel=lanczos3' \
  -F 'keepOriginalNames=true'

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/batch-resize

Parameters

Name	Type	Required	Description
imageFiles	fileupload required	Yes	—
width	number	No	—
height	number	No	—
fit	select	No	—
position	select	No	—
format	select	No	—
quality	number	No	—
preserveMetadata	checkbox	No	—
upscale	checkbox	No	—
kernel	select	No	—
keepOriginalNames	checkbox	No	—

File-type parameters must be uploaded first via POST /upload/batch-resize, 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-batch-resize": {
      "name": "batch-resize",
      "description": "Resize multiple images to specific dimensions with various resize options and batch processing",
      "baseUrl": "https://api.elysiatools.com/mcp/sse?toolId=batch-resize",
      "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": "batch-resize",
    "arguments": {
  "imageFiles": "https://example.com/file.ext",
  "width": 800,
  "height": 600,
  "fit": "cover",
  "position": "center",
  "format": "original",
  "quality": 85,
  "preserveMetadata": false,
  "upscale": false,
  "kernel": "lanczos3",
  "keepOriginalNames": true
}
  }
}

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]