search_available_models
Find AI models for image generation by searching with descriptive queries and optional style filters through the Replicate API.
Instructions
Search for available models matching the query.
Args:
query: Search query describing the desired model
style: Optional style to filter by
Returns:
List of matching models with scores
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | ||
| style | No |
Implementation Reference
- Handler function for the search_available_models tool. Searches Replicate models using the client, scores them based on popularity, featured status, version stability, tags matching style and image generation, sorts by score, and returns a ModelList.
async def search_available_models( query: str, style: str | None = None, ) -> ModelList: """Search for available models matching the query. Args: query: Search query describing the desired model style: Optional style to filter by Returns: List of matching models with scores """ search_query = query if style: search_query = f"{style} style {search_query}" async with ReplicateClient(api_token=os.getenv("REPLICATE_API_TOKEN")) as client: result = await client.search_models(search_query) models = [Model(**model) for model in result["models"]] # Score models but don't auto-select scored_models = [] for model in models: score = 0 run_count = getattr(model, "run_count", 0) or 0 score += min(50, (run_count / 1000) * 50) if getattr(model, "featured", False): score += 20 if model.latest_version: score += 10 tags = getattr(model, "tags", []) if style and any(style.lower() in tag.lower() for tag in tags): score += 15 if "image" in tags or "text-to-image" in tags: score += 15 scored_models.append((model, score)) # Sort by score but return all for user selection scored_models.sort(key=lambda x: x[1], reverse=True) return ModelList( models=[m[0] for m in scored_models], next_cursor=result.get("next_cursor"), total_count=result.get("total_count"), ) - src/mcp_server_replicate/server.py:927-927 (registration)The @mcp.tool() decorator registers the search_available_models function as an MCP tool with the function name.
async def search_available_models( - Pydantic model defining the output schema for search_available_models, used as return type.
github_url: Optional[str] = Field(None, description="URL to model's GitHub repository") paper_url: Optional[str] = Field(None, description="URL to model's research paper") license_url: Optional[str] = Field(None, description="URL to model's license") run_count: Optional[int] = Field(None, description="Number of times this model has been run") cover_image_url: Optional[str] = Field(None, description="URL to model's cover image") latest_version: Optional[ModelVersion] = Field(None, description="Latest version of the model")