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Houdini MCP

Houdini MCP

by beatreichenbach
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

sample_volume

Read named volume fields at world positions or at another SOP's points to sample volume data accurately.

Instructions

Read named volume fields at world positions, or at another SOP's points.

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_path": "<node_path>",
      "fields": "<fields>"
    },
    "name": "sample_volume"
  }
}

Input Schema

NameRequiredDescriptionDefault
binsNo
limitNo
fieldsYes
from_nodeNo
node_pathYes
positionsNo
thresholdNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.8/5.0
Behavior2/5

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

No annotations are supplied, so the description carries the full burden. 'Read' weakly implies non-destructive, but nothing is said about permissions, failure modes on missing fields or out-of-range positions, or how limit/bins affect results — significant gaps for a 7-parameter sampling tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single front-loaded sentence with no wasted words, but that brevity is achieved by omission rather than efficiency — it is undersized relative to a seven-parameter tool with two modes.

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

Completeness2/5

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

With no annotations, no output schema, seven undocumented parameters, and zero schema coverage, the description does far too little to let an agent call this correctly — it omits the meaning of bins, limit, threshold, and the return shape entirely.

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?

Schema description coverage is 0%, so the description must compensate, and it only vaguely gestures at three of seven parameters (fields, positions, from_node as 'another SOP's points'). bins, limit, and threshold receive no explanation at all, leaving the most consequential sampling controls undocumented.

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?

States a specific verb and resource: read named volume fields, with two sampling modes (world positions or another SOP's points). An agent can tell it is a sampling/read tool, though it never names a sibling such as get_volume_info to sharpen the boundary.

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 'or' construction implicitly signals two mutually exclusive modes of use (positions vs. from_node), but there is no explicit when-to-use guidance, no prerequisites, and no statement about which mode takes precedence or what happens if both are given.

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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