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search_polyhaven_assets

Search Polyhaven's library of 3D assets like HDRI environments, textures, and models, with filtering by type and categories to find resources for 3D projects.

Instructions

Search for assets on Polyhaven with optional filtering.

Parameters:
- asset_type: Type of assets to search for (hdris, textures, models, all)
- categories: Optional comma-separated list of categories to filter by

Returns a list of matching assets with basic information.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
asset_typeNoall
categoriesNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The handler function for the 'search_polyhaven_assets' MCP tool. It uses the Blender connection to send a 'search_polyhaven_assets' command with parameters and formats the returned assets list, sorting by popularity.
    @mcp.tool()
    def search_polyhaven_assets(
        ctx: Context, asset_type: str = "all", categories: str = None
    ) -> str:
        """
        Search for assets on Polyhaven with optional filtering.
    
        Parameters:
        - asset_type: Type of assets to search for (hdris, textures, models, all)
        - categories: Optional comma-separated list of categories to filter by
    
        Returns a list of matching assets with basic information.
        """
        try:
            blender = get_blender_connection()
            result = blender.send_command(
                "search_polyhaven_assets",
                {"asset_type": asset_type, "categories": categories},
            )
    
            if "error" in result:
                return f"Error: {result['error']}"
    
            # Format the assets in a more readable way
            assets = result["assets"]
            total_count = result["total_count"]
            returned_count = result["returned_count"]
    
            formatted_output = f"Found {total_count} assets"
            if categories:
                formatted_output += f" in categories: {categories}"
            formatted_output += f"\nShowing {returned_count} assets:\n\n"
    
            # Sort assets by download count (popularity)
            sorted_assets = sorted(
                assets.items(), key=lambda x: x[1].get("download_count", 0), reverse=True
            )
    
            for asset_id, asset_data in sorted_assets:
                formatted_output += (
                    f"- {asset_data.get('name', asset_id)} (ID: {asset_id})\n"
                )
                formatted_output += (
                    f"  Type: {['HDRI', 'Texture', 'Model'][asset_data.get('type', 0)]}\n"
                )
                formatted_output += (
                    f"  Categories: {', '.join(asset_data.get('categories', []))}\n"
                )
                formatted_output += (
                    f"  Downloads: {asset_data.get('download_count', 'Unknown')}\n\n"
                )
    
            return formatted_output
        except Exception as e:
            logger.error(f"Error searching Polyhaven assets: {str(e)}")
            return f"Error searching Polyhaven assets: {str(e)}"
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 'Returns a list of matching assets with basic information,' which hints at read-only behavior and output format, but lacks details on pagination, rate limits, authentication needs, or error handling. This is insufficient for a search tool with no annotation coverage, resulting in a significant gap.

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 well-structured and concise, with three sentences that efficiently cover purpose, parameters, and returns. Each sentence adds value without redundancy, and it is front-loaded with the core functionality. There is no wasted text, making it easy to parse quickly.

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 (2 parameters, no annotations, but with an output schema), the description is partially complete. It covers the purpose and parameters adequately, and the output schema likely handles return values, reducing the need for detailed output explanation. However, it lacks behavioral context and usage guidelines, leaving gaps in overall completeness.

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?

Schema description coverage is 0%, so the description must compensate. It adds meaningful context: 'asset_type' is explained with allowed values (hdris, textures, models, all), and 'categories' is described as an 'optional comma-separated list.' This clarifies parameter usage beyond the schema's basic titles, though it could provide more detail on category formats or examples.

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: 'Search for assets on Polyhaven with optional filtering.' It specifies the verb ('search'), resource ('assets on Polyhaven'), and scope ('with optional filtering'). However, it does not explicitly differentiate from sibling tools like 'download_polyhaven_asset' or 'get_polyhaven_categories', which reduces the score from a perfect 5.

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 mentions 'optional filtering' but does not specify scenarios, prerequisites, or exclusions. For example, it does not clarify if this should be used before downloading assets or as an alternative to browsing categories directly, leaving usage context implied at best.

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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