Recommend Model

Immutable Catalog Entry

This descriptor comes from the active versioned Portal catalog.

READleonardo-ai.leonardo_recommend_model

• Contract tier: agent_ready
• Risk: read
• Catalog version: leonardo-ai-2026.07.12.1
• Descriptor hash: 8ba25aca78f9915b9c1c1e7212529be6481a206d1446017c005ee066c8aa9730

Recommend a Leonardo model and default request body additions for a media goal. Runs locally and does not contact Leonardo.Ai.

Request Body

{
  "jsonrpc": "2.0",
  "id": "leonardo-ai-leonardo-recommend-model-example",
  "method": "tools/call",
  "params": {
    "name": "leonardo-ai.leonardo_recommend_model",
    "arguments": {
      "goal": "",
      "model": "",
      "prompt": "",
      "use_case": "use_case_example",
      "model_name": "",
      "target_medium": ""
    }
  }
}

Arguments Schema

{
  "type": "object",
  "properties": {
    "goal": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Alias for prompt/use_case when an agent describes the desired output."
    },
    "model": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Optional requested model name or provider identifier."
    },
    "prompt": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Optional prompt text for heuristic routing."
    },
    "use_case": {
      "type": "string",
      "default": "general",
      "description": "One of general, photorealistic, text, character, fast, video, or a free-form goal."
    },
    "model_name": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Optional human-readable requested model name."
    },
    "target_medium": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Optional medium context such as wallpaper, poster, or product shot."
    }
  },
  "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-recommend-model-example",
  "method": "tools/call",
  "params": {
    "name": "leonardo-ai.leonardo_recommend_model",
    "arguments": {
      "goal": "",
      "model": "",
      "prompt": "",
      "use_case": "use_case_example",
      "model_name": "",
      "target_medium": ""
    }
  }
}'

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-recommend-model-example",
  "method": "tools/call",
  "params": {
    "name": "leonardo-ai.leonardo_recommend_model",
    "arguments": {
      "goal": "",
      "model": "",
      "prompt": "",
      "use_case": "use_case_example",
      "model_name": "",
      "target_medium": ""
    }
  }
}),
});
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-recommend-model-example",
  "method": "tools/call",
  "params": {
    "name": "leonardo-ai.leonardo_recommend_model",
    "arguments": {
      "goal": "",
      "model": "",
      "prompt": "",
      "use_case": "use_case_example",
      "model_name": "",
      "target_medium": ""
    }
  }
}
response = requests.post(url, headers=headers, json=payload, timeout=60)
print(response.json())

Example Responses

200 Success

{
  "ok": true,
  "message": "Tool leonardo-ai.leonardo_recommend_model 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."
}