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rhino-mcp

by rokibul-mist
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Python
Hybrid

rhino_run_python

Execute Python code inside Rhino's runtime to automate geometry operations, analyze models, control Grasshopper, and run custom scripts on demand.

Instructions

    Execute arbitrary Python code inside Rhino's runtime environment.
    
    Args:
    code: Python source code string to execute.
    rhino_id: Optional Rhino instance ID (for multi-instance setups).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
codeYes
rhino_idNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.1/5.0
Behavior2/5

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

With no annotations available, the description carries the full burden of behavioral disclosure. It states that execution happens in Rhino's runtime and that code is arbitrary, but it does not mention potential document mutation, sandboxing, error behavior, or side effects, which is significant for an arbitrary code execution tool.

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 description is compact and front-loaded with the core purpose, and the Args section is concise yet informative. No unnecessary words or filler are present.

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?

Despite having an output schema, the tool is highly complex because it executes arbitrary code, yet the description omits execution environment details, available modules, safety caveats, and how it differs from rhino_execute_python or similar runners. This is insufficient for an agent to confidently select and invoke it in nontrivial scenarios.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema provides no descriptions, but the description's Args section explains both parameters: code is a Python source string, and rhino_id is an optional instance selector for multi-instance setups. This adds meaningful context beyond the raw schema types.

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 clearly states that the tool executes arbitrary Python code within Rhino's runtime environment, using a specific verb and resource. However, it does not differentiate itself from the sibling tool rhino_execute_python, which appears to serve a nearly identical purpose.

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 guidance is given about when to use this tool versus alternatives such as rhino_execute_python, rhino_run_macro, or rhino_run_command. The description offers no exclusions, prerequisites, or preferred use cases, leaving the agent without direction for selection.

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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