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vtkapi-mcp

vtkapi-mcp

by patrickoleary
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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vtk_get_class_visibility

Retrieves a visibility score (0.0-1.0) for a VTK class to indicate how likely it is to be used directly.

Instructions

Get the visibility score of a VTK class (0.0-1.0). Higher scores indicate classes more likely to be used directly.

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": {
      "class_name": "<class_name>"
    },
    "name": "vtk_get_class_visibility"
  }
}

Input Schema

NameRequiredDescriptionDefault
class_nameYesVTK class name (e.g., 'vtkPolyDataMapper')

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior4/5

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

The description explains the output range and interpretation, which goes beyond the input schema. Since annotations are absent, this adequately informs the agent of the return value nature, though no error or edge case behavior is mentioned.

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 a single sentence with no extraneous words. It efficiently conveys purpose, range, and interpretation.

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

Completeness4/5

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

For a simple one-parameter tool with no output schema, the description provides essential context (range and meaning). It lacks details on error handling or response format, but given the complexity, it is largely complete.

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?

Schema description coverage is 100% with a clear example for class_name. The description adds no further parameter meaning; baseline 3 is appropriate as the schema already documents the parameter sufficiently.

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 states the tool retrieves a visibility score (0.0-1.0) and interprets higher scores as more likely to be used directly. This specific metric differentiates it from sibling tools that return documentation, methods, or synopsis.

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?

No explicit when-to-use or when-not-to-use guidance is provided. While the purpose is clear, the description does not mention alternatives or contexts where this metric is appropriate, leaving inference to the agent.

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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