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Houdini MCP

Houdini MCP

by beatreichenbach
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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find_nearest_point

Locate the nearest point or points in a Houdini geometry node to a specified position, optionally returning multiple results from that node.

Instructions

Find the nearest point(s) to a given position.

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>",
      "position": "<position>"
    },
    "name": "find_nearest_point"
  }
}

Input Schema

NameRequiredDescriptionDefault
positionYes
node_pathYes
max_resultsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.6/5.0
Behavior2/5

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

No annotations exist, so the description carries the full behavioral burden and does almost none of it. It never states the coordinate space or units of 'position', what happens when node_path is invalid, whether an empty result is possible, how ties or distances are reported, or whether results are sorted by distance.

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 short sentence with no wasted words and the operation front-loaded, but its brevity comes at the cost of under-specification rather than from efficient information density.

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 three parameters, zero schema descriptions, no annotations, and no output schema, the definition omits too much for an agent to call it correctly. It lacks the coordinate space, distance semantics, node-path requirements, and result shape that this spatial query needs.

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 barely does. The '(s)' hints that max_results controls multiplicity and 'to a given position' loosely maps to position, but node_path is completely unexplained — which node type, whether it must contain geometry, and what path syntax is expected.

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: find the nearest point(s) to a given position. That is clearly different from listing tools like find_nodes or find_error_nodes, but it never names an alternative or clarifies what a 'point' is (geometry points inside a node's geometry, presumably, given the node_path parameter).

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

Usage Guidelines2/5

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

There is no guidance on when to use this versus find_nodes or the other query tools, no prerequisites, and no exclusions. The agent must infer the whole usage context from the name alone.

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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