search_sketchfab_models
Find downloadable 3D models on Sketchfab for Blender projects using search queries and category filters.
Instructions
Search for models on Sketchfab with optional filtering.
Parameters:
query: Text to search for
categories: Optional comma-separated list of categories
count: Maximum number of results to return (default 20)
downloadable: Whether to include only downloadable models (default True)
Returns a formatted list of matching models.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | ||
| categories | No | ||
| count | No | ||
| downloadable | No |
Implementation Reference
- src/blender_mcp/server.py:518-563 (handler)The search_sketchfab_models tool handler, which uses the blender connection to perform the search.
@mcp.tool() def search_sketchfab_models( ctx: Context, query: str, categories: str = None, count: int = 20, downloadable: bool = True ) -> str: """ Search for models on Sketchfab with optional filtering. Parameters: - query: Text to search for - categories: Optional comma-separated list of categories - count: Maximum number of results to return (default 20) - downloadable: Whether to include only downloadable models (default True) Returns a formatted list of matching models. """ try: blender = get_blender_connection() logger.info(f"Searching Sketchfab models with query: {query}, categories: {categories}, count: {count}, downloadable: {downloadable}") result = blender.send_command("search_sketchfab_models", { "query": query, "categories": categories, "count": count, "downloadable": downloadable }) if "error" in result: logger.error(f"Error from Sketchfab search: {result['error']}") return f"Error: {result['error']}" # Safely get results with fallbacks for None if result is None: logger.error("Received None result from Sketchfab search") return "Error: Received no response from Sketchfab search" # Format the results models = result.get("results", []) or [] if not models: return f"No models found matching '{query}'" formatted_output = f"Found {len(models)} models matching '{query}':\n\n" for model in models: