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aras-plm-mcp

aras-plm-mcp

by Erryb95
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

aras_list_queries

Retrieve predefined Aras Innovator Query Builder queries for reuse in PLM processes and operations.

Instructions

Query salvate del Query Builder. Sono interrogazioni preconfezionate che Aras usa internamente e che puoi riusare, es. 'PE_BomStructure' o 'Aras.Resolution.LatestReleased'.

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": "aras_list_queries"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior3/5

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

With no annotations provided, the description largely carries the behavioral disclosure burden. It adds useful context—these are internal Aras queries available for reuse—but does not state whether the tool returns all queries, includes system queries, or any listing details. The behavior is predictable (a list operation), so the gap is moderate.

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?

Two short sentences with no redundancy. The resource type is front-loaded and the examples add practical value. Every word contributes.

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 zero-parameter list tool, the description covers what is being listed and gives representative example query names. It could be more explicit about the return value or that it lists all available queries, but it is sufficient for an agent to know what this tool provides before calling it.

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 has zero parameters, so per the rubric the baseline is 4. The description does not need to explain parameter semantics since there are none.

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 clearly states a specific resource: saved Query Builder queries ('Query salvate del Query Builder'). It gives concrete examples like 'PE_BomStructure' and 'Aras.Resolution.LatestReleased', making the subject unmistakable. However, it does not explicitly differentiate from the similar sibling aras_list_saved_searches.

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?

The description explains these are pre-packaged queries that Aras uses internally and that the agent can reuse, implying this tool is for discovering reusable queries. It does not mention when to prefer aras_list_queries over aras_list_saved_searches or aras_describe_query, leaving the selection 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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