Upload Reference Image

Immutable Catalog Entry

This descriptor comes from the active versioned Portal catalog.

WRITEleonardo-ai.leonardo_upload_reference_image

• Contract tier: agent_ready
• Risk: write
• Catalog version: leonardo-ai-2026.07.12.1
• Descriptor hash: 823610481454ab7a63600612d035c33789aec93109fffbf10eeb5927961ac30f

Upload a reference image from URL, local file path, data URL, or base64. Accepts optional metadata for agent-side traceability. Requires the request-scoped x-leonardo-api-key Portal field and contacts Leonardo.Ai.

Request Body

{
  "jsonrpc": "2.0",
  "id": "leonardo-ai-leonardo-upload-reference-image-example",
  "method": "tools/call",
  "params": {
    "name": "leonardo-ai.leonardo_upload_reference_image",
    "arguments": {
      "body": "",
      "file": "",
      "name": "",
      "target": "init_image",
      "data_url": "",
      "filename": "",
      "metadata": "",
      "extension": "",
      "file_path": "",
      "image_url": ""
    }
  }
}

Arguments Schema

{
  "type": "object",
  "properties": {
    "body": {
      "anyOf": [
        {
          "type": "object",
          "additionalProperties": true
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Optional Leonardo request body additions using provider parameter names exactly."
    },
    "file": {
      "anyOf": [
        {
          "type": "object",
          "additionalProperties": true
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Optional ChatGPT/OpenAI file object. When provided, the server uses download_url, url, file_path, local_file_path, filename, and mime_type from the object when present."
    },
    "name": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Optional agent-side label for this upload, such as a scene or asset name. This is not sent to Leonardo's upload-init JSON body."
    },
    "target": {
      "enum": [
        "init_image",
        "canvas_init_image",
        "dataset_image",
        "media"
      ],
      "type": "string",
      "default": "init_image",
      "description": "Leonardo upload target."
    },
    "data_url": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Base64 data URL to upload."
    },
    "filename": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Optional original filename for multipart upload metadata and extension inference. This is not sent to the Leonardo upload-init JSON body."
    },
    "metadata": {
      "anyOf": [
        {
          "type": "object",
          "additionalProperties": true
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Optional agent-side metadata to echo in the response for traceability. Leonardo's upload-init endpoint only accepts extension, so metadata is not forwarded to the provider."
    },
    "extension": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "png, jpg, jpeg, or webp. Required for base64_data."
    },
    "file_path": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Local file path on the MCP server/container to upload. The path must be inside LEONARDO_LOCAL_UPLOAD_ROOTS, which defaults to /uploads, /tmp, and /data/uploads."
    },
    "image_url": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Remote HTTPS image URL to download and upload as a reference image."
    },
    "mime_type": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Optional MIME type such as image/png, image/jpeg, or image/webp for extension inference. This is not sent to the Leonardo upload-init JSON body."
    },
    "dataset_id": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Required when target is dataset_image."
    },
    "base64_data": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Raw base64 image content to upload."
    },
    "request_body": {
      "anyOf": [
        {
          "type": "object",
          "additionalProperties": true
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Optional Leonardo request body additions using provider parameter names exactly."
    },
    "local_file_path": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Alias for file_path for agents that use a local_file_path name."
    }
  },
  "additionalProperties": false
}

Output Schema

{
  "type": "object",
  "description": "Leonardo MCP result. ok=false, provider_ok=false, a failed status, or an error field represents a semantic failure even when transport delivery succeeded.",
  "additionalProperties": true
}

Code Examples

cURL

curl -X POST 'https://portal.madpanda3d.com/api/mcp' \
  -H 'Authorization: Bearer mad_live_***' \
  -H 'Content-Type: application/json' \
  -d '{
  "jsonrpc": "2.0",
  "id": "leonardo-ai-leonardo-upload-reference-image-example",
  "method": "tools/call",
  "params": {
    "name": "leonardo-ai.leonardo_upload_reference_image",
    "arguments": {
      "body": "",
      "file": "",
      "name": "",
      "target": "init_image",
      "data_url": "",
      "filename": "",
      "metadata": "",
      "extension": "",
      "file_path": "",
      "image_url": ""
    }
  }
}'

Node.js

const response = await fetch('https://portal.madpanda3d.com/api/mcp', {
  method: 'POST',
  headers: {
    Authorization: 'Bearer mad_live_***',
    'Content-Type': 'application/json',
  },
  body: JSON.stringify({
  "jsonrpc": "2.0",
  "id": "leonardo-ai-leonardo-upload-reference-image-example",
  "method": "tools/call",
  "params": {
    "name": "leonardo-ai.leonardo_upload_reference_image",
    "arguments": {
      "body": "",
      "file": "",
      "name": "",
      "target": "init_image",
      "data_url": "",
      "filename": "",
      "metadata": "",
      "extension": "",
      "file_path": "",
      "image_url": ""
    }
  }
}),
});
const data = await response.json();
console.log(data);

Python

import requests

url = 'https://portal.madpanda3d.com/api/mcp'
headers = {
    'Authorization': 'Bearer mad_live_***',
    'Content-Type': 'application/json',
}
payload = {
  "jsonrpc": "2.0",
  "id": "leonardo-ai-leonardo-upload-reference-image-example",
  "method": "tools/call",
  "params": {
    "name": "leonardo-ai.leonardo_upload_reference_image",
    "arguments": {
      "body": "",
      "file": "",
      "name": "",
      "target": "init_image",
      "data_url": "",
      "filename": "",
      "metadata": "",
      "extension": "",
      "file_path": "",
      "image_url": ""
    }
  }
}
response = requests.post(url, headers=headers, json=payload, timeout=60)
print(response.json())

Example Responses

200 Success

{
  "ok": true,
  "message": "Tool leonardo-ai.leonardo_upload_reference_image executed successfully.",
  "note": "Response shape varies by MCP tool. Inspect live responses for exact fields."
}

502 Upstream Error

{
  "ok": false,
  "classification": "upstream_http_error",
  "message": "Upstream MCP returned a non-success status."
}