@placraftic/mcp-server

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list_finishings

Retrieve 3D printing post-processing services (vapor smoothing, painting, support removal, sanding) with pricing. Filter by technology like FDM, SLA, or SLS.

Instructions

List all available post-processing and finishing services (vapor smoothing, painting, support removal, sanding) with pricing

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_finishings"
  }
}

Input Schema

Name	Required	Description	Default
`technology`	No	Filter finishing operations by technology code (e.g. 'fdm', 'sla', 'sls')

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 11, 2026

TDQS

A3.5/5.0

Behavior3/5

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

No annotations are supplied, so the description carries the full burden. It does disclose that pricing is included in the response, which is useful return-value context, but says nothing about auth requirements, pagination, or whether the catalog is studio-scoped. For a simple read-only list this is adequate but not rich.

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?

One sentence, front-loaded with the verb and resource, and the parenthetical examples earn their place by clarifying the domain. Slightly dense but no wasted framing.

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?

There is no output schema, so the description must hint at returns — and it does via 'with pricing', the most salient field. For a zero-required-param list tool with a fully documented filter, this is nearly complete; only return shape/pagination detail is missing.

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 single 'technology' filter has 100% schema description coverage with an example enum-style list ('fdm', 'sla', 'sls'), so the schema does the heavy lifting. The description never mentions filtering at all, so it adds nothing beyond the schema — baseline 3 is correct.

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 resource (finishing services) and enumerates concrete examples (vapor smoothing, painting, support removal, sanding) plus the 'with pricing' payload. It is clearly distinguishable from the singular get_finishing sibling, though it never names that sibling explicitly.

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?

Usage is only implied — an agent can infer this is the browse/discovery call for finishing options before drilling into get_finishing. There is no explicit when-to-use, when-not-to-use, or named alternative, so it falls at the 'implied usage' level.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.