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maya_vision3d

Generate 3D assets from images or text prompts via a GPU-powered Vision3D server. Start jobs, poll progress, and download results.

Instructions

AI-powered 3D asset generation via Vision3D server (requires GPU with Hunyuan3D-2).

Server selection is fully per-session and runtime-only: the first action that needs a GPU call returns vision3d_url_required. The LLM must ask the user for the Vision3D URL in the chat and then call select_server with that URL. Nothing is persisted to disk — the URL lives only in process memory until the MCP server restarts.

After selection, jobs are non-blocking: start → poll → download.

Available actions:

• select_server — Set the Vision3D server URL for the rest of the session. Required params: {"url": "http://..."}. Accepts any valid http/https URL; ask the user first. • health — Check if the selected Vision3D server is running and what GPU/models are available. No params. • generate_image — Start 3D generation from a reference image. Required params: {"image_path": "/path/to/image.png", "output_subdir": "my_asset"} Optional: {"preset": "medium", "model": "turbo", "octree_resolution": 384, "num_inference_steps": 20, "target_faces": 50000} • generate_text — Start 3D generation from a text prompt. Required params: {"text_prompt": "a medieval sword", "output_subdir": "sword"} Optional: {"preset": "medium", "model": "turbo", "octree_resolution": 384, "num_inference_steps": 20, "target_faces": 50000} • texture — Texture an existing mesh using a reference image. Required params: {"output_subdir": "my_asset"} Optional: {"mesh_filename": "mesh.glb", "image_filename": "input.png"} • poll — Check job progress (call repeatedly while running). Required params: {"job_id": "uuid-from-generate"} • download — Download completed job results. Required params: {"job_id": "uuid", "output_subdir": "my_asset"} Optional: {"files": ["textured.glb", "mesh.glb"]}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Discloses key traits: GPU requirement, no persistence (URL only in memory), non-blocking jobs. Missing details on error handling, whether it modifies the Maya scene, or output cleanup, but still highly informative.

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?

Well-structured with bullet points for each action and a clear workflow. Slightly verbose (multiple paragraphs) but earns its length by covering all necessary details.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Covers the entire pipeline from server selection to download, including async behavior. No gaps in understanding how to use this complex tool.

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

Parameters5/5

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

Despite 0% schema coverage (schema only defines dispatch structure), the description fully documents each action's parameters with examples (e.g., 'Required params: {"image_path": ...}'). Compensates completely for lack of schema detail.

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 identifies it as 'AI-powered 3D asset generation via Vision3D server' and lists all sub-actions (select_server, health, generate_image, etc.). Distinct from sibling Maya tools (e.g., maya_create_primitive) which focus on direct scene manipulation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicit workflow: first select_server (ask user for URL), then start generation, poll, download. States 'jobs are non-blocking: start → poll → download' and provides required/optional params for each action.

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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