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Houdini MCP

Houdini MCP

by beatreichenbach
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

get_simulation_info

Retrieve the cooked simulation state of a Houdini DOP network at the current frame to inspect or debug simulation data by node path.

Instructions

Get DOP network simulation state, cooked at the current frame.

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>"
    },
    "name": "get_simulation_info"
  }
}

Input Schema

NameRequiredDescriptionDefault
node_pathYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. The phrase 'cooked at the current frame' does add real behavioral information — it implies the network is evaluated/cooked at the current frame rather than returning a cached snapshot — but nothing is said about side effects, return shape, or whether cooking mutates state.

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?

A single tight sentence-fragment with the key qualifier front-loaded and no filler. It is efficient, though its brevity contributes to the semantic gaps noted elsewhere.

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, and an entirely undocumented parameter, the description should explain what simulation state is returned and how node_path is interpreted. As written, an agent knows the general intent but not enough to call it with confidence.

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 needs to compensate for node_path and does not. It never clarifies that node_path identifies the DOP network itself (as opposed to a SOP/OBJ node), nor what path format 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?

Specific verb (Get) plus a specific resource (DOP network simulation state) and a temporal qualifier (cooked at the current frame). An agent can distinguish this from reset_simulation and step_simulation, though it does not explicitly contrast itself with the get_dop_* siblings.

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?

No statement of when to use this instead of step_simulation, reset_simulation, or get_dop_object/get_dop_field. The agent must infer that this reads whole-network simulation state as opposed to inspecting individual DOP objects or fields.

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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