get_model_details
Retrieve detailed specifications and configuration data for AI models to verify compatibility and understand capabilities before deployment.
Instructions
Get detailed information about a specific model.
Args:
model_id: Model identifier in format owner/name
Returns:
Detailed model information
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| model_id | Yes |
Implementation Reference
- src/mcp_server_replicate/tools/model_tools.py:61-64 (registration)Registration of the 'get_model_details' tool using the @mcp.tool decorator, specifying the name and description.
@mcp.tool( name="get_model_details", description="Get detailed information about a specific model.", ) - The handler function implements the logic to retrieve detailed model information by parsing the model_id, querying the owner's models via ReplicateClient, falling back to search if not found, and returning a Model object or raising ValueError.
async def get_model_details(model_id: str) -> Model: """Get detailed information about a specific model. Args: model_id: Model identifier in format 'owner/model' Returns: Model object containing detailed model information Raises: RuntimeError: If the Replicate client fails to initialize ValueError: If the model is not found Exception: If the API request fails """ owner, name = model_id.split("/") async with ReplicateClient() as client: # First try to find the model in the owner's models result = client.list_models(owner=owner) for model in result["models"]: if model["name"] == name: return Model(**model) # If not found, try searching for it search_result = await client.search_models(model_id) for model in search_result["models"]: if f"{model['owner']}/{model['name']}" == model_id: return Model(**model) raise ValueError(f"Model not found: {model_id}")