qidi-mcp

get_filament_presets

Read-onlyIdempotent

Retrieve the printer's built-in QIDI filament profiles and recommended drying temperature and time for each material so you can answer how to dry a spool.

Instructions

QIDI's built-in filament profiles as configured on this printer, including the recommended drying temperature and time per material from the machine's own drying table. Useful for answering 'how should I dry this spool?'.

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": "get_filament_presets"
  }
}

Input Schema

Name	Required	Description	Default
No arguments

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv2.0.1Nov 9, 2026

TDQS

A3.6/5.0

Behavior3/5

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

The readOnlyHint and idempotentHint annotations already establish that this is a safe, repeatable read, so the description does not need to restate safety. It adds useful provenance — the values come from the machine's own drying table rather than a generic database — but says nothing about result volume or whether presets can be machine- or material-specific.

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?

Two tight sentences: the first identifies the data and its source, the second anchors the practical use case. Nothing is redundant, though the phrasing 'QIDI's built-in filament profiles' is slightly repetitive alongside 'from the machine's own drying table'.

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?

With an output schema present, the description need not enumerate return fields, and with no inputs there is nothing else to document. The remaining small gap is the lack of sibling disambiguation for an agent choosing between this and the box filament listing tools.

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 there is no parameter semantics to explain and the baseline of 4 applies. The description correctly implies the call is unfiltered, returning all presets configured on this printer.

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 names a specific resource (QIDI built-in filament profiles as configured on this printer) and states the payload includes recommended drying temperature and time per material. That is concrete and agent-usable. It stops short of differentiating itself from the closest sibling, list_box_filament_options, so it is clear but not fully disambiguated.

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?

It gives an implied use case via the quoted question 'how should I dry this spool?', which tells an agent when this tool is a good fit. However, it offers no exclusions and never states how it differs from sibling filament tools such as list_box_filament_options or set_box_slot_filaments, leaving routing to inference.

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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