Server definition

Hash: sha256:c148853a59bc80434efa1e5e16ff0b82e564e38e3bbe28a0bb4e96a80ab12770
What it is: What a remote MCP server returned when asked what it offers: 4 tools

The blob, as servednamed by its sha256

{
  "instructions": "Image Processing API suite with 3 capabilities:\n1. **Background Removal** -- remove_background removes the background from images.\n2. **Image Upscaling** -- upscale_image enhances image resolution using Real-ESRGAN (2x-4x).\n3. **Face Restoration** -- restore_face restores and enhances faces using GFPGAN.\n\nAll tools accept/return base64-encoded images.",
  "tools": [
    {
      "description": "Check health status of Image API services and loaded models.\n\nReturns:\n    dict with keys:\n        - status (str): 'healthy' or error state\n        - models (dict): Loaded model status per capability\n        - version (str): API version",
      "inputSchema": {
        "properties": {},
        "type": "object"
      },
      "name": "check_image_service",
      "outputSchema": null
    },
    {
      "description": "Remove the background from an image.\n\nUses BiRefNet segmentation to precisely separate foreground from background.\nReturns a base64-encoded image with transparent background (PNG) or white\nbackground (WebP). Sub-500ms latency on GPU.\n\nArgs:\n    image_base64: Base64-encoded image data (PNG, JPEG, or WebP).\n    output_format: Output format -- 'png' (with transparency) or 'webp'.\n\nReturns:\n    dict with keys:\n        - image_base64 (str): Base64-encoded result image\n        - format (str): Output image format\n        - original_size (dict): Original width and height\n        - processing_ms (int): Processing time in milliseconds",
      "inputSchema": {
        "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"
        ],
        "type": "object"
      },
      "name": "remove_background",
      "outputSchema": null
    },
    {
      "description": "Restore and enhance faces in an image using GFPGAN.\n\nDetects all faces via RetinaFace, restores quality (fixes blur, noise,\ncompression artifacts), and pastes them back. Optionally enhances the\nbackground using Real-ESRGAN. GPU-accelerated, sub-3s latency.\n\nArgs:\n    image_base64: Base64-encoded image data containing faces (PNG, JPEG, WebP).\n    upscale: Output upscale factor -- 1 to 4 (default: 2).\n    enhance_background: Whether to enhance background with Real-ESRGAN (default: true).\n\nReturns:\n    dict with keys:\n        - image (str): Base64-encoded restored image\n        - format (str): Output image format\n        - width (int): Output width\n        - height (int): Output height\n        - upscale (int): Scale factor applied\n        - processing_time_ms (float): Processing time in milliseconds",
      "inputSchema": {
        "properties": {
          "enhance_background": {
            "default": true,
            "description": "Enhance background with Real-ESRGAN (default: true)",
            "type": "boolean"
          },
          "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"
          }
        },
        "required": [
          "image_base64"
        ],
        "type": "object"
      },
      "name": "restore_face",
      "outputSchema": null
    },
    {
      "description": "Upscale image resolution using Real-ESRGAN.\n\nEnhances image resolution by 2x or 4x using GPU-accelerated Real-ESRGAN\nsuper-resolution. Processes in tiles (256x256) to manage VRAM.\nMaximum output dimension: 8192x8192.\n\nArgs:\n    image_base64: Base64-encoded image data (PNG, JPEG, or WebP).\n    scale: Upscale factor -- 2 or 4 (default: 4).\n\nReturns:\n    dict with keys:\n        - image (str): Base64-encoded upscaled image\n        - format (str): Output image format\n        - width (int): Output width\n        - height (int): Output height\n        - scale (int): Scale factor applied\n        - processing_time_ms (float): Processing time in milliseconds",
      "inputSchema": {
        "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"
        ],
        "type": "object"
      },
      "name": "upscale_image",
      "outputSchema": null
    }
  ]
}

Verify it yourself

curl -s https://api.teppi.xyz/v1/evidence/sha256:c148853a59bc80434efa1e5e16ff0b82e564e38e3bbe28a0bb4e96a80ab12770 | sha256sum