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get_polyhaven_categories

Retrieve available categories for Poly Haven assets to organize and filter 3D resources in Blender. Supports HDRI, textures, and models.

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 handler function for the 'get_polyhaven_categories' tool. It checks if PolyHaven is enabled, sends the command to the Blender addon via socket, formats the categories by sorting them by count, and returns a formatted 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)}"
  • The @mcp.tool() decorator registers the get_polyhaven_categories function as an MCP tool.
    @mcp.tool()
  • The function signature and docstring define the input schema (asset_type: str, default 'hdris') and output as str.
    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)
        """
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states it 'Get[s] a list of categories', implying a read-only operation, but doesn't clarify aspects like rate limits, authentication needs, or what the returned list format might be (e.g., JSON structure, pagination). This leaves significant gaps for a tool with no 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 appropriately sized and front-loaded, starting with the core purpose followed by parameter details. Both sentences earn their place by clarifying the tool's function and its single parameter, with no redundant or verbose language.

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 purpose and parameter semantics but lacks behavioral details and usage guidelines, making it incomplete for optimal agent understanding despite the simple context.

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 beyond the input schema, which has 0% description coverage. It explains that 'asset_type' specifies 'the type of asset to get categories for' and lists possible values (hdris, textures, models, all), providing essential semantic information not present in the schema's bare title 'Asset Type' and default 'hdris'.

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 verb ('Get') and resource ('list of categories for a specific asset type on Polyhaven'), making the purpose understandable. However, it doesn't explicitly differentiate this tool from its siblings like 'search_polyhaven_assets' or 'get_polyhaven_status', which could have overlapping or related functions.

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 where fetching categories is necessary or how it relates to sibling tools like 'search_polyhaven_assets', leaving the agent to infer usage context.

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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