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Maya MCP

Maya MCP

by science-animated
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

get_attribute

Retrieves the current value of a specified attribute on a Maya node, so you can inspect scene properties by node and attribute name.

Instructions

Get the value of an attribute on a Maya node. Example: node='pCube1', attribute='tx'.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "node": "<node>",
      "attribute": "<attribute>"
    },
    "name": "get_attribute"
  }
}

Input Schema

NameRequiredDescriptionDefault
nodeYes
attributeYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations, the description carries the behavioral burden. 'Get' implies a read-only operation, and the example clarifies the basic call shape, but it does not mention error behavior for missing nodes/attributes or confirm the absence of side effects.

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?

Two sentences, front-loaded with the purpose, and the example earns its place by illustrating both parameters. There is no wasted text.

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?

The tool is simple with two required strings and an output schema, so explanation of return values is unnecessary. The description and example are nearly sufficient, lacking only error-behavior details for an invalid node or attribute.

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 0%, so the description must compensate. The example maps both parameters ('node' to a node name, 'attribute' to a short attribute name like 'tx'), which adds useful meaning, but it does not document long names, nested attributes, or format expectations.

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 states a specific verb and resource: 'Get the value of an attribute on a Maya node.' That clearly distinguishes it from set_attribute and list_attributes, though it does not name those siblings explicitly.

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

Usage Guidelines3/5

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

The example implies when to use it (reading a single attribute like 'tx' from 'pCube1'), but there is no explicit guidance on when to prefer get_transform, get_object_info, or list_attributes instead. Usage is implied rather than stated.

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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