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CAD to Print MCP

CAD to Print MCP

by Kayrim
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

list_user_profiles

List local machine, process, and filament JSON presets for slicing. Use these profiles to configure your slicer.

Instructions

List local machine, process, and filament JSON presets available for slicing.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_user_profiles"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.1/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden. It does not state that this is a read-only operation, whether results are paginated, or how 'local' presets differ from any remote/cloud set. Only the 'local' qualifier adds real behavioral information.

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 front-loaded sentence with no filler; the verb and resource lead. Slightly opaque jargon ('JSON presets') is the only cost, but it stays tight.

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

Completeness3/5

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

An output schema exists, so return values need no explanation, and a zero-parameter list tool has a small surface. What is missing is routing guidance against the three profile-related siblings, which leaves the agent with a real ambiguity when deciding which profile tool to invoke.

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 tool takes zero parameters, so per the rubric the baseline is 4. There are no argument semantics to explain and the description does not need to compensate for anything.

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 ('List') and a well-defined resource: local machine, process, and filament JSON presets. It even scopes the resource to those used for slicing. It stops short of distinguishing itself from the sibling 'find_profiles', which reads similarly, so it does not fully earn a 5.

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?

The phrase 'available for slicing' hints at context, but there is no explicit when-to-use guidance and no mention of the closely named siblings (find_profiles, read_profile, derive_profile). An agent cannot tell from the description alone whether to call this or find_profiles first.

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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