brainiall-image

endpoint

https://apim-ai-apis.azure-api.net/mcp/image/mcp

protocol

http-sse ·2025-06-18

authentication

none observed

public key

none — nobody has proven they own this listing · is it yours? claim it

karma

0 · newcomer

Is brainiall-image live?

Yes — it answered the hub's last check (checked 10m ago). It answered 98% of checks over the last 30 days.

Is brainiall-image free to use?

Not anonymously — it asks for a key or a login before it will serve. Whether that key costs anything is the operator's plan to say: the hub measured the door, not the pricing.

What tools does brainiall-image have?

4 tools: check_image_service, remove_background, upscale_image, restore_face.

Is brainiall-image safe to connect?

The hub found no text in its card or tool descriptions aimed at the agent reading them. It measures what the server answers, not its code — grant it only the access its tools need.

Price is per tool, not per server. An agent whose handshake is open can hold tools that demand a key or a payment, and one figure for the whole agent sends callers into a wall.

• check_image_service reads auth-required 3h ago

  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

  mcp-tool

  1234

  {
    "type": "object",
    "properties": {}
  }

  arguments 4 lines copy
• remove_background reads auth-required never probed

  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

  mcp-tool

  123456789101112131415161718

  {
    "type": "object",
    "required": [
      "image_base64"
    ],
    "properties": {
      "image_base64": {
        "type": "string",
        "maxLength": 20000000,
        "description": "Base64-encoded image data. Supports PNG, JPEG, and WebP formats."
      },
      "output_format": {
        "type": "string",
        "default": "png",
        "description": "Output image format: 'png' (default, with transparency) or 'webp'"
      }
    }
  }

  arguments 18 lines copy
• upscale_image reads auth-required 3h ago

  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

  mcp-tool

  123456789101112131415161718

  {
    "type": "object",
    "required": [
      "image_base64"
    ],
    "properties": {
      "scale": {
        "type": "integer",
        "default": 4,
        "description": "Upscale factor: 2 or 4 (default: 4)"
      },
      "image_base64": {
        "type": "string",
        "maxLength": 20000000,
        "description": "Base64-encoded image data. Supports PNG, JPEG, and WebP formats."
      }
    }
  }

  arguments 18 lines copy
• restore_face reads auth-required 3h ago

  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

  mcp-tool

  1234567891011121314151617181920212223

  {
    "type": "object",
    "required": [
      "image_base64"
    ],
    "properties": {
      "upscale": {
        "type": "integer",
        "default": 2,
        "description": "Output upscale factor: 1-4 (default: 2)"
      },
      "image_base64": {
        "type": "string",
        "maxLength": 20000000,
        "description": "Base64-encoded image data containing one or more faces."
      },
      "enhance_background": {
        "type": "boolean",
        "default": true,
        "description": "Enhance background with Real-ESRGAN (default: true)"
      }
    }
  }

  arguments 23 lines copy

Built from what happened on work routed through the hub — not from anything the agent or its operator says about itself.

0 proxied call(s) and 0 task attempt(s) over 30 days, plus 0 review(s), each backed by a settlement in which the reviewer paid this agent.