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search_sketchfab_models

Find and filter 3D models from Sketchfab for use in Blender projects, supporting category selection and downloadable content.

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 'search_sketchfab_models' tool. It decorates with @mcp.tool() for registration, defines input parameters (schema), formats search results from Blender addon response.
    @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 asset_creation_strategy prompt includes instructions on using search_sketchfab_models as part of the preferred workflow for model asset creation, after checking Sketchfab status.
    @mcp.prompt()
    def asset_creation_strategy() -> str:
        """Defines the preferred strategy for creating assets in Blender"""
        return """When creating 3D content in Blender, always start by checking if integrations are available:
    
        0. Before anything, always check the scene from get_scene_info()
        1. First use the following tools to verify if the following integrations are enabled:
            1. PolyHaven
                Use get_polyhaven_status() to verify its status
                If PolyHaven is enabled:
                - For objects/models: Use download_polyhaven_asset() with asset_type="models"
                - For materials/textures: Use download_polyhaven_asset() with asset_type="textures"
                - For environment lighting: Use download_polyhaven_asset() with asset_type="hdris"
            2. Sketchfab
                Sketchfab is good at Realistic models, and has a wider variety of models than PolyHaven.
                Use get_sketchfab_status() to verify its status
                If Sketchfab is enabled:
                - 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
            3. Hyper3D(Rodin)
                Hyper3D Rodin is good at generating 3D models for single item.
                So don't try to:
                1. Generate the whole scene with one shot
                2. Generate ground using Hyper3D
                3. Generate parts of the items separately and put them together afterwards
    
                Use get_hyper3d_status() to verify its status
                If Hyper3D is enabled:
                - For objects/models, do the following steps:
                    1. Create the model generation task
                        - Use generate_hyper3d_model_via_images() if image(s) is/are given
                        - Use generate_hyper3d_model_via_text() if generating 3D asset using text prompt
                        If key type is free_trial and insufficient balance error returned, tell the user that the free trial key can only generated limited models everyday, they can choose to:
                        - Wait for another day and try again
                        - Go to hyper3d.ai to find out how to get their own API key
                        - Go to fal.ai to get their own private API key
                    2. Poll the status
                        - Use poll_rodin_job_status() to check if the generation task has completed or failed
                    3. Import the asset
                        - Use import_generated_asset() to import the generated GLB model the asset
                    4. After importing the asset, ALWAYS check the world_bounding_box of the imported mesh, and adjust the mesh's location and size
                        Adjust the imported mesh's location, scale, rotation, so that the mesh is on the right spot.
    
                    You can reuse assets previous generated by running python code to duplicate the object, without creating another generation task.
    
        3. Always check the world_bounding_box for each item so that:
            - Ensure that all objects that should not be clipping are not clipping.
            - Items have right spatial relationship.
        
        4. Recommended asset source priority:
            - For specific existing objects: First try Sketchfab, then PolyHaven
            - For generic objects/furniture: First try PolyHaven, then Sketchfab
            - For custom or unique items not available in libraries: Use Hyper3D Rodin
            - For environment lighting: Use PolyHaven HDRIs
            - For materials/textures: Use PolyHaven textures
    
        Only fall back to scripting when:
        - PolyHaven, Sketchfab, and Hyper3D are all disabled
        - A simple primitive is explicitly requested
        - No suitable asset exists in any of the libraries
        - Hyper3D Rodin failed to generate the desired asset
        - The task specifically requires a basic material/color
        """
  • The @mcp.tool() decorator registers the search_sketchfab_models function as an MCP tool.
    @mcp.tool()

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.0.0
    • addedInput schema / title
      Added value: +"search_sketchfab_modelsArguments"
  2. 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.