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get_polyhaven_categories

Retrieve available categories for Polyhaven assets to organize 3D resources in Blender. Specify asset type (hdris, textures, models) to filter categories for efficient asset management.

Instructions

Get a list of categories for a specific asset type on Polyhaven.

Parameters:

  • asset_type: The type of asset to get categories for (hdris, textures, models, all)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
asset_typeNohdris

Implementation Reference

  • The main handler function for the 'get_polyhaven_categories' MCP tool. It checks if PolyHaven is enabled, sends the command to the Blender addon socket server, receives and parses the JSON response, formats the categories sorted by asset count, and returns a readable string list.
    @mcp.tool()
    def get_polyhaven_categories(ctx: Context, asset_type: str = "hdris") -> str:
        """
        Get a list of categories for a specific asset type on Polyhaven.
        
        Parameters:
        - asset_type: The type of asset to get categories for (hdris, textures, models, all)
        """
        try:
            blender = get_blender_connection()
            if not _polyhaven_enabled:
                return "PolyHaven integration is disabled. Select it in the sidebar in BlenderMCP, then run it again."
            result = blender.send_command("get_polyhaven_categories", {"asset_type": asset_type})
            
            if "error" in result:
                return f"Error: {result['error']}"
            
            # Format the categories in a more readable way
            categories = result["categories"]
            formatted_output = f"Categories for {asset_type}:\n\n"
            
            # Sort categories by count (descending)
            sorted_categories = sorted(categories.items(), key=lambda x: x[1], reverse=True)
            
            for category, count in sorted_categories:
                formatted_output += f"- {category}: {count} assets\n"
            
            return formatted_output
        except Exception as e:
            logger.error(f"Error getting Polyhaven categories: {str(e)}")
            return f"Error getting Polyhaven categories: {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 only states the basic action ('Get a list of categories') without mentioning any behavioral traits such as rate limits, authentication needs, response format, or potential errors. For a tool with zero annotation coverage, this is inadequate, as it leaves critical operational details unspecified.

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 appropriately sized and front-loaded, with the core purpose stated first followed by parameter details. Both sentences earn their place by clarifying the tool's function and parameter options. It avoids unnecessary fluff, making it efficient, though minor improvements in structure (e.g., bullet points for parameters) could enhance readability.

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 low complexity (1 parameter, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose and parameter semantics but lacks details on behavioral traits, usage context, and output format. Without annotations or output schema, the description should do more to compensate, but it meets the bare minimum for a simple read operation, hence a score of 3.

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 meaningful context for the single parameter 'asset_type' by listing possible values (hdris, textures, models, all), which is not covered in the input schema (0% schema description coverage). This compensates well for the schema gap, providing clear semantics beyond the schema's basic type and title. However, it doesn't explain the implications of choosing 'all' or other nuances, preventing a perfect score.

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: 'Get a list of categories for a specific asset type on Polyhaven.' This specifies the verb ('Get'), resource ('list of categories'), and context ('on Polyhaven'). However, it doesn't explicitly differentiate from sibling tools like 'search_polyhaven_assets' or 'get_polyhaven_status', which is why it's not a 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 the asset_type parameter but doesn't explain scenarios for using this tool over other Polyhaven-related tools like 'search_polyhaven_assets' or general context for category retrieval. This lack of explicit when/when-not or alternative references results in a low score.

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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