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ujs204

BlenderMCP

by ujs204

search_polyhaven_assets

Search for 3D assets on Polyhaven to find HDRI environments, textures, or models for use in Blender 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

Implementation Reference

  • The handler function for the 'search_polyhaven_assets' MCP tool. It sends a 'search_polyhaven_assets' command to the Blender addon via socket connection, processes the response, sorts assets by download count, and formats a detailed list of matching assets for display.
    @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)}"
  • The @mcp.tool() decorator registers the search_polyhaven_assets function as an MCP tool.
    @mcp.tool()
  • The function signature and docstring define the input schema (asset_type and categories parameters) and output as a formatted string.
    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.
        """
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. It mentions optional filtering and returns a list with basic information, but doesn't disclose critical behaviors like pagination, rate limits, authentication needs, error handling, or what 'basic information' includes. For a search tool with no annotation coverage, this is insufficient.

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. The parameter explanations are clear and necessary. It could be slightly more concise by integrating the return statement into the opening sentence, but overall it's efficient with minimal waste.

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 2 parameters with 0% schema coverage and no output schema, the description does a decent job explaining parameters but lacks completeness. It doesn't cover return format details, error cases, or behavioral aspects like search limits. For a search tool with no annotations, it's adequate but has clear gaps.

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' can be hdris, textures, models, or all, and 'categories' is a comma-separated list for filtering. This compensates well for the schema's lack of descriptions, though it doesn't detail format examples or constraints.

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 searches for assets on Polyhaven with filtering, which is a specific verb+resource combination. It distinguishes itself from sibling tools like 'download_polyhaven_asset' or 'search_sketchfab_models' by specifying the Polyhaven platform. However, it doesn't explicitly contrast with 'get_polyhaven_categories' which might be related.

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 doesn't mention when to prefer this over 'search_sketchfab_models' for different asset types, or how it relates to 'get_polyhaven_categories' for filtering. Usage is implied by the search functionality but lacks explicit 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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