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download_sketchfab_model

Download and import Sketchfab 3D models into Blender using their unique identifier (UID) for AI-assisted 3D modeling and scene creation.

Instructions

Download and import a Sketchfab model by its UID.

Parameters:

  • uid: The unique identifier of the Sketchfab model

Returns a message indicating success or failure. The model must be downloadable and you must have proper access rights.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
uidYes

Implementation Reference

  • The core handler function for the 'download_sketchfab_model' tool. It is decorated with @mcp.tool() for registration and implements the logic by sending a socket command to the Blender addon with the model UID, then parsing and returning the result.
    @mcp.tool()
    def download_sketchfab_model(
        ctx: Context,
        uid: str
    ) -> str:
        """
        Download and import a Sketchfab model by its UID.
        
        Parameters:
        - uid: The unique identifier of the Sketchfab model
        
        Returns a message indicating success or failure.
        The model must be downloadable and you must have proper access rights.
        """
        try:
            
            blender = get_blender_connection()
            logger.info(f"Attempting to download Sketchfab model with UID: {uid}")
            
            result = blender.send_command("download_sketchfab_model", {
                "uid": uid
            })
            
            if result is None:
                logger.error("Received None result from Sketchfab download")
                return "Error: Received no response from Sketchfab download request"
                
            if "error" in result:
                logger.error(f"Error from Sketchfab download: {result['error']}")
                return f"Error: {result['error']}"
            
            if result.get("success"):
                imported_objects = result.get("imported_objects", [])
                object_names = ", ".join(imported_objects) if imported_objects else "none"
                return f"Successfully imported model. Created objects: {object_names}"
            else:
                return f"Failed to download model: {result.get('message', 'Unknown error')}"
        except Exception as e:
            logger.error(f"Error downloading Sketchfab model: {str(e)}")
            import traceback
            logger.error(traceback.format_exc())
            return f"Error downloading Sketchfab model: {str(e)}"
  • Input/output schema and description provided in the function docstring, defining the 'uid' parameter as required string input.
    """
    Download and import a Sketchfab model by its UID.
    
    Parameters:
    - uid: The unique identifier of the Sketchfab model
    
    Returns a message indicating success or failure.
    The model must be downloadable and you must have proper access rights.
    """
  • The @mcp.tool() decorator registers this function as an MCP tool.
    @mcp.tool()
  • Companion 'search_sketchfab_models' tool used to find model UIDs before downloading with download_sketchfab_model.
    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)}"
  • Helper tool to check if Sketchfab integration (required for download_sketchfab_model) is enabled.
    @mcp.tool()
    def get_sketchfab_status(ctx: Context) -> str:
        """
        Check if Sketchfab integration is enabled in Blender.
        Returns a message indicating whether Sketchfab features are available.
        """
        try:
            blender = get_blender_connection()
            result = blender.send_command("get_sketchfab_status")
            enabled = result.get("enabled", False)
            message = result.get("message", "")
            if enabled:
                message += "Sketchfab is good at Realistic models, and has a wider variety of models than PolyHaven."        
            return message
        except Exception as e:
            logger.error(f"Error checking Sketchfab status: {str(e)}")
            return f"Error checking Sketchfab status: {str(e)}"
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions access rights and downloadability as prerequisites, but doesn't describe what happens during import (e.g., file format, destination, potential side effects), error conditions, or response format beyond a success/failure message. This is inadequate for a mutation tool with zero annotation coverage.

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

Conciseness4/5

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

The description is efficiently structured with a clear purpose statement followed by parameter and return information. It avoids unnecessary words, though the prerequisites could be integrated more smoothly. Every sentence serves a functional purpose.

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

Completeness2/5

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

For a mutation tool with no annotations, no output schema, and a single parameter, the description is incomplete. It lacks details on import behavior (e.g., where files go, supported formats), error handling, and doesn't fully compensate for the missing structured data, leaving the agent with significant uncertainty.

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

Parameters3/5

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

The description explicitly documents the single parameter ('uid: The unique identifier of the Sketchfab model'), which adds value since schema description coverage is 0%. However, it doesn't provide format examples, constraints, or where to find the UID, leaving some semantic gaps.

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 ('Download and import') and the resource ('a Sketchfab model by its UID'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'search_sketchfab_models' or 'import_generated_asset', which would be needed for a perfect score.

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 mentions prerequisites ('The model must be downloadable and you must have proper access rights'), but provides no guidance on when to use this tool versus alternatives like 'import_generated_asset' or 'search_sketchfab_models'. It lacks explicit when/when-not instructions or named alternatives.

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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