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AI Image Smart Enhance

Intelligently analyze and enhance image quality using AI vision models

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/ai-image-enhance' \
  -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-image-enhance' \
  -F 'imageFile=uploads/2026/01/01/your-tool-1700000000000-abc123.ext' \
  -F 'enhancementType=auto' \
  -F 'userGoal=e.g., Make the sky bluer, keep skin tones natural...' \
  -F 'outputFormat=jpeg' \
  -F 'quality=92'

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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-image-enhance

Parameters

NameTypeRequiredDescription
imageFilefileupload requiredYesSupports JPG, PNG, WebP, BMP, TIFF and other common image formats
enhancementTypeselectNoSelect enhancement type, auto detect will intelligently adjust based on image content
userGoaltextNoDescribe the specific effect you want to achieve
outputFormatselectNoJPEG for photos, PNG for images with transparency
qualityrangeNoOutput image quality (1-100), only for JPEG and WebP
File-type parameters must be uploaded first via POST /upload/ai-image-enhance, 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-ai-image-enhance": {
      "name": "ai-image-enhance",
      "description": "Intelligently analyze and enhance image quality using AI vision models",
      "baseUrl": "https://api.elysiatools.com/mcp/sse?toolId=ai-image-enhance",
      "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-image-enhance",
    "arguments": {
  "imageFile": "https://example.com/file.ext",
  "enhancementType": "auto",
  "userGoal": "e.g., Make the sky bluer, keep skin tones natural...",
  "outputFormat": "jpeg",
  "quality": 92
}
  }
}
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]

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