Skip to main content
Glama

generate_hyper3d_model_via_images

Converts input images into a 3D model with materials using Hyper3D and imports it into Blender for further editing.

Instructions

Generate 3D asset using Hyper3D by giving images of the wanted asset, and import the generated asset into Blender.
The 3D asset has built-in materials.
The generated model has a normalized size, so re-scaling after generation can be useful.

Parameters:
- input_image_paths: The **absolute** paths of input images. Even if only one image is provided, wrap it into a list. Required if Hyper3D Rodin in MAIN_SITE mode.
- input_image_urls: The URLs of input images. Even if only one image is provided, wrap it into a list. Required if Hyper3D Rodin in FAL_AI mode.
- bbox_condition: Optional. If given, it has to be a list of ints of length 3. Controls the ratio between [Length, Width, Height] of the model.

Only one of {input_image_paths, input_image_urls} should be given at a time, depending on the Hyper3D Rodin's current mode.
Returns a message indicating success or failure.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
user_promptNo
bbox_conditionNo
input_image_urlsNo
input_image_pathsNo
Behavior3/5

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

The description mentions that models have built-in materials and normalized size, and that re-scaling is useful. It says the tool returns a success/failure message. Since no annotations are provided, the description carries full burden but lacks details on error handling, authentication needs, or potential destructive actions.

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 fairly concise and structured: it starts with the main purpose, then lists parameters in a clear format. It avoids irrelevant detail. The omission of user_prompt is a minor structural flaw.

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?

For a tool with four parameters, moderate complexity, and no output schema, the description provides a decent overview of the generation process and parameter usage. However, the missing parameter documentation and lack of detail on failure modes or output format make it incomplete.

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

Parameters2/5

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

With 0% schema coverage, the description must fully document parameters. It describes input_image_paths, input_image_urls, and bbox_condition with specific format expectations (absolute paths, list wrapping, int array of length 3). However, it completely omits the user_prompt parameter, leaving it undocumented despite being present in the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool generates a 3D asset using Hyper3D from images and imports it into Blender. It distinguishes itself from siblings like generate_hyper3d_model_via_text, which uses text prompts, and other tools for downloading or status.

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 description explains that only one of input_image_paths or input_image_urls should be provided depending on the Hyper3D Rodin mode, and notes bbox_condition as optional. However, it does not explicitly compare to alternatives like generate_hyper3d_model_via_text or state when to choose this over text-based generation.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Apteryx-T/blender_mcp_test'

If you have feedback or need assistance with the MCP directory API, please join our Discord server