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omniverse-mcp

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capture_viewport

Read-only

Captures the Omniverse viewport and saves a PNG plus bounding-box and segmentation files so you can map visible prims to screen pixels and understand the scene.

Instructions

Capture the viewport and save 3 files for scene understanding:

    1. **Viewport image** (PNG) -- what the camera sees
    2. **Bounding boxes** (TXT) -- screen-space bounding boxes mapping each visible prim to pixel coordinates
    3. **Instance segmentation** (PNG) -- each prim rendered as a unique color, with a legend mapping colors to prim paths

    Use files 2 and 3 to understand which prim is where in the viewport image.
    Set include_image=True to return the viewport image inline (uses more context but lets you see the scene directly).

Input Schema

NameRequiredDescriptionDefault
widthNoImage width in pixels
heightNoImage height in pixels
camera_pathNoThe camera prim to capture from; the active one when empty
include_imageNoAlso return the image inline, besides the file (uses more context)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.2

TDQS

A4.1/5.0
Behavior4/5

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

Annotations declare readOnlyHint=true, which is consistent with a capture operation, and the description goes beyond that by disclosing the side effect of writing three files to disk and their contents. It also warns that include_image increases context usage — useful behavior not in the annotations. The save location of the files is not stated, a minor gap.

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?

Front-loaded with the action and result, then a numbered breakdown that is easy to scan. It is longer than strictly necessary but every line conveys a distinct output artifact, so there is little waste.

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

Completeness4/5

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

Output schema is absent, and the description compensates by fully explaining the three returned files and the inline-image option. The only missing detail is where the files land on disk, which an agent would need to actually consume them.

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 coverage is 100%, so width, height, camera_path, and include_image are each documented in the schema. The description reinforces include_image's trade-off but adds nothing beyond the schema's own text, so baseline 3 applies.

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?

Specific verb (capture) plus resource (viewport) with a precise enumeration of the three artifacts produced. An agent immediately knows this tool produces visual + spatial data as opposed to any sibling like dump_scene or get_scene_tree.

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?

Explicitly tells the agent how to combine the outputs ('Use files 2 and 3 to understand which prim is where') and gives a clear condition for include_image=True with its context cost trade-off. It does not name alternative sibling tools for scene inspection, but the usage context is unambiguous.

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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