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Houdini MCP

Houdini MCP

by beatreichenbach
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

frame_all

Frames all geometry in the Houdini viewport, or focuses the view on specified nodes or a bounding box for inspection.

Instructions

Frame all geometry in the viewport, or only some nodes or a box.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "frame_all"
  }
}

Input Schema

NameRequiredDescriptionDefault
boundsNo
pane_nameNo
node_pathsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.5/5.0
Behavior2/5

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

With zero annotations, the description bears the entire burden of transparency, yet it offers no behavioral traits beyond functional scope. It provides no information regarding execution time, required permissions, or potential failure modes for this view operation.

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?

The definition is highly concise, delivering its complete functionality in a single, punchy sentence. There is no superfluous language, and the core differentiation is front-loaded.

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?

The description is moderately complete for a view manipulation tool. However, due to the lack of input/output schemas and annotations, crucial details remain missing, such as the required format for defining 'a box' or the expected return value structure.

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?

Given 0% schema coverage, the description must compensate significantly. It successfully links the abstract parameters to functional outcomes (e.g., using the concept of 'a box' to guide parameter selection), but it does not define the structural requirements of the input data itself.

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 defines the core action ('Frame') and the scope, distinguishing between framing 'all geometry' versus a subset of 'some nodes or a box.' This high level of specificity makes the purpose unambiguous.

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 tool description implies its scope (all vs. specific nodes/box) but fails to offer guidance on when to use it compared to sibling tools like frame_selection or cook_frame_range. It describes capability rather than providing explicit usage rules.

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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