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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

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior3/5

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

With no annotations, the description carries the burden of behavioral disclosure. It mentions that the tool returns a formatted list of matching models, which is helpful, but it does not disclose whether it calls an external API, potential rate limits, pagination behavior, or error conditions. The read-only nature is implied by 'search' but not made explicit.

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 concise and front-loaded with the core purpose, followed by a clean bullet-style parameter list. Every sentence adds value and there is no redundant or filler content.

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?

The parameter documentation is complete, but the return value is only described as a 'formatted list', which is vague given that no output schema exists. Missing details include what fields each model entry contains, how categories combine, and what happens on errors or empty results. It is adequate for a basic search tool, but not fully complete.

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

Parameters5/5

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

The schema description coverage is 0%, but the description compensates fully by explaining every parameter: query text, comma-separated categories, maximum result count, and downloadable filtering. This goes well beyond the bare schema definitions and gives the agent actionable meaning.

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 action ('Search for models on Sketchfab') and the resource, making the tool's purpose immediately understandable. It does not explicitly contrast itself with sibling tools, but the verb 'search' naturally distinguishes it from download, preview, and status tools.

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

Usage Guidelines4/5

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

The opening sentence gives clear context for when to use the tool: to search Sketchfab for models. It does not provide explicit exclusions or alternatives, but the sibling tool names make it evident that this is the search step before downloading or previewing.

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