Server definition

Hash: sha256:0a4ba87a3e702e9c29ee7571208f5475f212efb11bad747ebab1d9965e47bb9a
What it is: What a remote MCP server returned when asked what it offers: 10 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 with the Brainiall image-upscaling engine (2x-4x).\n3. **Face Restoration** -- restore_face restores and enhances faces with the Brainiall face-restoration engine.\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": "Turn a document image into structured fields. doc_type picks the schema (receipt/invoice/id/contract/form/generic).\n\nA page with no readable text returns an error rather than a guess.\n\nReturns:\n    dict with keys: doc_type (str), fields (dict — null for any value not present), text (str — the recognised plain text).",
      "inputSchema": {
        "properties": {
          "doc_type": {
            "default": "generic",
            "description": "The document kind — picks the field schema: receipt | invoice | id | contract | form | generic | business_card | w2 | health_card | mortgage | pay_stub",
            "type": "string"
          },
          "image": {
            "description": "Base64-encoded PNG/JPEG of a single document page",
            "type": "string"
          }
        },
        "required": [
          "image"
        ],
        "type": "object"
      },
      "name": "document_extract",
      "outputSchema": null
    },
    {
      "description": "Ask a natural-language question about a document image; returns a grounded answer plus the supporting line.\n\nReturns found:false rather than guessing when the document doesn't contain the answer.\n\nReturns:\n    dict with keys: answer (str|null), found (bool), supporting_text (str|null), text (str).",
      "inputSchema": {
        "properties": {
          "image": {
            "description": "Base64-encoded PNG/JPEG of the document page",
            "type": "string"
          },
          "question": {
            "description": "The natural-language question about the document",
            "maxLength": 1000,
            "type": "string"
          }
        },
        "required": [
          "image",
          "question"
        ],
        "type": "object"
      },
      "name": "document_query",
      "outputSchema": null
    },
    {
      "description": "Reconstruct every table in a document image into headers and rows.\n\nReturns:\n    dict with keys: table_count (int), tables (list of {title, headers, rows, row_count, column_count}); [] if there are no tables.",
      "inputSchema": {
        "properties": {
          "image": {
            "description": "Base64-encoded PNG/JPEG of the document page",
            "type": "string"
          }
        },
        "required": [
          "image"
        ],
        "type": "object"
      },
      "name": "document_tables",
      "outputSchema": null
    },
    {
      "description": "Return the document as structured Markdown (headings, tables, lists, code blocks, math).\n\nBrainiall Doc Layout engine. The single API for converting documents to LLM-friendly format.",
      "inputSchema": {
        "properties": {
          "page_range": {
            "anyOf": [
              {
                "type": "string"
              },
              {
                "type": "null"
              }
            ],
            "default": null,
            "description": "Page range like '1,2,5-10' or null for all pages"
          },
          "pdf": {
            "description": "Base64-encoded PDF document",
            "type": "string"
          }
        },
        "required": [
          "pdf"
        ],
        "type": "object"
      },
      "name": "document_to_markdown",
      "outputSchema": null
    },
    {
      "description": "Remove the background from an image.\n\nUses Brainiall Cutout engine 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 with the Brainiall face-restoration engine.\n\nDetects all faces via RetinaFace, restores quality (fixes blur, noise,\ncompression artifacts), and pastes them back. Optionally enhances the\nbackground with the Brainiall image-upscaling engine. 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 the Brainiall image-upscaling engine (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 the Brainiall image-upscaling engine (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": "Run a multi-skill enrichment pipeline over a document image or text in one call.\n\nBrainiall Skillsets engine. Returns per-skill outputs ready for indexing or RAG.",
      "inputSchema": {
        "properties": {
          "image": {
            "anyOf": [
              {
                "type": "string"
              },
              {
                "type": "null"
              }
            ],
            "default": null,
            "description": "Base64 image (triggers OCR)"
          },
          "skills": {
            "anyOf": [
              {
                "items": {
                  "type": "string"
                },
                "type": "array"
              },
              {
                "type": "null"
              }
            ],
            "default": null,
            "description": "Enrichment skills: ocr | entities | language | keyphrases | sentiment"
          },
          "text": {
            "anyOf": [
              {
                "type": "string"
              },
              {
                "type": "null"
              }
            ],
            "default": null,
            "description": "Pre-extracted text (skip OCR)"
          }
        },
        "type": "object"
      },
      "name": "run_skillsets",
      "outputSchema": null
    },
    {
      "description": "Multimodal extraction. Send an image, text, or both; define your schema of fields; get structured JSON.\n\nBrainiall Content Understanding engine. Unified multimodal field extraction over images and text.",
      "inputSchema": {
        "properties": {
          "field_schema": {
            "anyOf": [
              {
                "additionalProperties": true,
                "type": "object"
              },
              {
                "type": "null"
              }
            ],
            "default": null,
            "description": "Map of field_name -> description, e.g. {\"invoice_id\":\"invoice number\",\"total\":\"amount due\"}"
          },
          "image": {
            "anyOf": [
              {
                "type": "string"
              },
              {
                "type": "null"
              }
            ],
            "default": null,
            "description": "Optional base64 image (will OCR first)"
          },
          "text": {
            "anyOf": [
              {
                "type": "string"
              },
              {
                "type": "null"
              }
            ],
            "default": null,
            "description": "Optional pre-extracted text"
          }
        },
        "type": "object"
      },
      "name": "understand_content",
      "outputSchema": null
    },
    {
      "description": "Upscale image resolution with the Brainiall image-upscaling engine.\n\nEnhances image resolution by 2x or 4x with the GPU-accelerated Brainiall image-upscaling engine\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
    }
  ]
}

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