Image Tools - Background Removal, Upscaling & Face Restoration
Background removal, 4x upscaling, and face restoration via GPU
使うべきか
品質と安全性
ツール定義とプロトコルへの準拠に関する自動分析に基づいています。
コンテキストコスト
これは、サーバーのツールがモデルのコンテキストに読み込まれるたびに消費されるおおよそのトークン数です。数が多いほど、ほかのタスクに使える注意が減ります。
インストール
ワンクリックインストール
これを `claude_desktop_config.json` ファイルに追加してください:
{
"mcpServers": {
"image-tools": {
"url": "https://image-mcp.thankfulfield-a7857897.eastus.azurecontainerapps.io/mcp"
}
}
}リモートエンドポイント
https://image-mcp.thankfulfield-a7857897.eastus.azurecontainerapps.io/mcpstreamable-httphttps://apim-ai-apis.azure-api.net/mcp/image/mcpstreamable-httpできること
ツール一覧
ツール（4）
🟢remove_background(image_base64, output_format)
Remove the background from an image. Uses BiRefNet segmentation to precisely separate foreground from background. Returns a base64-encoded image with transparent background (PNG) or white background (WebP). Sub-500ms latency on GPU. Args: image_base64: Base64-encoded image data (PNG, JPEG, or WebP). output_format: Output format -- 'png' (with transparency) or 'webp'. Returns: dict with keys: - image_base64 (str): Base64-encoded result image - format (str): Output image format - original_size (dict): Original width and height - processing_ms (int): Processing time in milliseconds
入力スキーマ
{
"type": "object",
"properties": {
"image_base64": {
"description": "Base64-encoded image data. Supports PNG, JPEG, and WebP formats.",
"maxLength": 20000000,
"type": "string"
},
"output_format": {
"default": "png",
"description": "Output image format: 'png' (default, with transparency) or 'webp'",
"type": "string"
}
},
"required": [
"image_base64"
]
}🟢upscale_image(image_base64, scale)
Upscale image resolution using Real-ESRGAN. Enhances image resolution by 2x or 4x using GPU-accelerated Real-ESRGAN super-resolution. Processes in tiles (256x256) to manage VRAM. Maximum output dimension: 8192x8192. Args: image_base64: Base64-encoded image data (PNG, JPEG, or WebP). scale: Upscale factor -- 2 or 4 (default: 4). Returns: dict with keys: - image (str): Base64-encoded upscaled image - format (str): Output image format - width (int): Output width - height (int): Output height - scale (int): Scale factor applied - processing_time_ms (float): Processing time in milliseconds
入力スキーマ
{
"type": "object",
"properties": {
"image_base64": {
"description": "Base64-encoded image data. Supports PNG, JPEG, and WebP formats.",
"maxLength": 20000000,
"type": "string"
},
"scale": {
"default": 4,
"description": "Upscale factor: 2 or 4 (default: 4)",
"type": "integer"
}
},
"required": [
"image_base64"
]
}🟢restore_face(image_base64, upscale, enhance_background)
Restore and enhance faces in an image using GFPGAN. Detects all faces via RetinaFace, restores quality (fixes blur, noise, compression artifacts), and pastes them back. Optionally enhances the background using Real-ESRGAN. GPU-accelerated, sub-3s latency. Args: image_base64: Base64-encoded image data containing faces (PNG, JPEG, WebP). upscale: Output upscale factor -- 1 to 4 (default: 2). enhance_background: Whether to enhance background with Real-ESRGAN (default: true). Returns: dict with keys: - image (str): Base64-encoded restored image - format (str): Output image format - width (int): Output width - height (int): Output height - upscale (int): Scale factor applied - processing_time_ms (float): Processing time in milliseconds
入力スキーマ
{
"type": "object",
"properties": {
"image_base64": {
"description": "Base64-encoded image data containing one or more faces.",
"maxLength": 20000000,
"type": "string"
},
"upscale": {
"default": 2,
"description": "Output upscale factor: 1-4 (default: 2)",
"type": "integer"
},
"enhance_background": {
"default": true,
"description": "Enhance background with Real-ESRGAN (default: true)",
"type": "boolean"
}
},
"required": [
"image_base64"
]
}🟢check_image_service
Check health status of Image API services and loaded models. Returns: dict with keys: - status (str): 'healthy' or error state - models (dict): Loaded model status per capability - version (str): API version
入力スキーマ
{
"type": "object",
"properties": {}
}コミュニティ
エビデンス