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vtkapi-mcp

vtkapi-mcp

by patrickoleary
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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vtk_get_class_semantic_methods

Retrieves the semantic methods of a VTK class by excluding dunder, private, and infrastructure methods, providing only relevant callables for API validation.

Instructions

Get non-boilerplate callable methods for a VTK class. Excludes dunder methods, private methods, and VTK infrastructure methods.

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_semantic_methods"
  }
}

Input Schema

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

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.3/5.0
Behavior4/5

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

No annotations are provided, so the description carries the burden. It clearly discloses that dunder, private, and infrastructure methods are excluded, which is key behavioral information for a retrieval 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 a single, clear sentence that is front-loaded with the verb and resource. Every word adds value, and it is concise without being under-specified.

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

Completeness5/5

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

For a simple retrieval tool with one parameter and no output schema, the description is complete. It explains the return value (non-boilerplate methods) and exclusions, making it sufficient for an agent to select and invoke correctly.

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?

The schema covers 100% of parameters with a description of class_name. The tool's description does not add additional meaning beyond the schema, so baseline score of 3 is appropriate.

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's purpose: getting non-boilerplate callable methods for a VTK class. It specifies what is excluded (dunder, private, infrastructure methods), distinguishing it from siblings like vtk_get_class_methods.

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

Usage Guidelines4/5

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

The description implies when to use this tool (when only public, meaningful methods are needed) by specifying exclusions. It does not explicitly mention alternatives like vtk_get_class_methods, but the sibling list provides context.

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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