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BlenderMCP

search_sketchfab_models

Find and filter 3D models from Sketchfab for use in Blender projects. Search by query, category, and downloadability to locate suitable assets.

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
NameRequiredDescriptionDefault
queryYes
categoriesNo
countNo
downloadableNo

Implementation Reference

  • The handler function for the 'search_sketchfab_models' MCP tool. It is registered via @mcp.tool() decorator. The function sends the search parameters to the Blender addon via socket command 'search_sketchfab_models' and formats the response into a readable string list of models.
    @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:
                if model is None:
                    continue
                    
                model_name = model.get("name", "Unnamed model")
                model_uid = model.get("uid", "Unknown ID")
                formatted_output += f"- {model_name} (UID: {model_uid})\n"
                
                # Get user info with safety checks
                user = model.get("user") or {}
                username = user.get("username", "Unknown author") if isinstance(user, dict) else "Unknown author"
                formatted_output += f"  Author: {username}\n"
                
                # Get license info with safety checks
                license_data = model.get("license") or {}
                license_label = license_data.get("label", "Unknown") if isinstance(license_data, dict) else "Unknown"
                formatted_output += f"  License: {license_label}\n"
                
                # Add face count and downloadable status
                face_count = model.get("faceCount", "Unknown")
                is_downloadable = "Yes" if model.get("isDownloadable") else "No"
                formatted_output += f"  Face count: {face_count}\n"
                formatted_output += f"  Downloadable: {is_downloadable}\n\n"
            
            return formatted_output
        except Exception as e:
            logger.error(f"Error searching Sketchfab models: {str(e)}")
            import traceback
            logger.error(traceback.format_exc())
            return f"Error searching Sketchfab models: {str(e)}"
  • The @mcp.tool() decorator registers the search_sketchfab_models function as an MCP tool.
    @mcp.tool()
  • Docstring defining the input parameters (schema) and return type for the tool.
    """
    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.
    """
  • Instructions in the asset_creation_strategy prompt on how to use the search_sketchfab_models tool.
    - For objects/models: First search using search_sketchfab_models() with your query
    - Then download specific models using download_sketchfab_model() with the UID
    - Note that only downloadable models can be accessed, and API key must be properly configured
    - Sketchfab has a wider variety of models than PolyHaven, especially for specific subjects
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions that it 'Returns a formatted list of matching models,' which gives some output context, but lacks details on rate limits, authentication needs, pagination, error handling, or what 'formatted list' entails. For a search tool with zero annotation coverage, this is insufficient.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately sized and front-loaded: the first sentence states the core purpose, followed by a bulleted list of parameters with clear explanations. Every sentence earns its place, with no redundant information or fluff. The structure is efficient and easy to parse.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity (4 parameters, no annotations, no output schema), the description is partially complete. It covers parameter semantics well but lacks behavioral context like error handling or output format details. For a search tool, this is adequate but leaves gaps in understanding how results are returned or what limitations exist.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description adds significant meaning beyond the input schema, which has 0% description coverage. It explains each parameter's purpose: 'query' as text to search for, 'categories' as optional comma-separated list, 'count' as maximum results with default 20, and 'downloadable' as filter with default True. This compensates well for the schema's lack of descriptions, though it doesn't cover format details like category values.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose as 'Search for models on Sketchfab with optional filtering,' which specifies the verb (search), resource (models on Sketchfab), and scope (optional filtering). It distinguishes from siblings like download_sketchfab_model or search_polyhaven_assets by focusing on Sketchfab models. However, it doesn't explicitly differentiate from other search tools beyond the platform name.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention when to prefer this over search_polyhaven_assets or other search-related tools, nor does it specify prerequisites or exclusions. The only implied usage is for searching Sketchfab models, but no contextual boundaries are defined.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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