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blender_fetch_asset

Fetch a 3D asset by ID from a library, such as an HDRI, texture, or model, and apply it directly to your Blender scene. For HDRIs, automatically set it as world lighting for instant realistic renders.

Instructions

Download an asset from a library by id, and optionally use it.

An HDRI becomes the world lighting in one call, which is the fastest route to a believable render without any HDRI hunting.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYes
typeNoAsset category, must match the search.hdris
libraryNopolyhaven
rotationNo
strengthNo
resolutionNo1k, 2k, 4k, 8k for HDRIs; 1k/2k/4k for textures.1k
set_as_worldNoFor HDRIs, wire it into the world shader automatically.
into_collectionNoFor models, import into this collection.
response_formatNo'markdown' for readable output, 'json' for raw structured data.markdown

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv4.4.0

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already provide readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds useful behavior by explaining that an HDRI becomes the world lighting and that the asset can be optionally used. It does not describe side effects for textures/models in detail, but the central behavior is disclosed and consistent with annotations.

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 short and front-loaded, with the core action stated first and the HDRI value proposition in a compact second paragraph. Every sentence earns its place, and there is no redundant repetition of the tool name or schema fields.

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 HDRI path is well covered, but the description remains vague about textures and models: what 'use' means for those asset types, what the tool returns, and how it relates to searching or downloading. With 9 parameters and no output schema, additional context would be needed for an agent to invoke it correctly across all asset categories.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 56%, so the description needs to add some param semantics. It reinforces the meaning of id and library and clarifies the HDRI/world-lighting behavior linked to type and set_as_world. However, parameters like rotation and strength have no description coverage in the schema and are also not explained in the description.

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 uses a specific verb and resource ('Download an asset from a library by id') and clarifies that the asset may optionally be used afterward. It is clear, but it does not explicitly differentiate this tool from sibling tools such as blender_download or blender_import_asset.

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 HDRI sentence provides a concrete use case: fetching an HDRI and making it the world lighting in one call is the fastest route to a believable render. It gives clear context for when to use it, though it does not name alternatives or state when not to use it.

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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