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aras-plm-mcp

aras-plm-mcp

by Erryb95
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

aras_search

Search for Aras PLM items across multiple types (Part, Document, ECR, etc.) using a keyword, returning matching records with type-specific details.

Instructions

Ricerca trasversale su piu' ItemType contemporaneamente: cerca un termine nei campi testuali (codice, nome, descrizione, titolo) di Part, Document, CAD, ECR, ECN, fornitori. Da usare quando NON sai in che tipo si trovi cio' che cerchi — Aras non ha una ricerca globale.

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": {
      "term": "<term>"
    },
    "name": "aras_search"
  }
}

Input Schema

NameRequiredDescriptionDefault
termYesTermine da cercare, es. 'girante', 'PMP-21', 'cavitazione'
perTypeNoMassimo risultati per tipo
itemTypesNoTipi da interrogare; default: Part, Document, CAD, ECR, ECN, Manufacturer, Manufacturer Part

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior4/5

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

No annotations are present, so the description carries the full burden. It clearly frames the operation as a read-only text search and details the scope of what is searched. A 5 would require an explicit statement about non-mutation or auth, but for a search tool the disclosure is adequate.

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 two sentences with zero filler, and the tool's core purpose is front-loaded. Every sentence adds scope, field details, or usage guidance.

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 straightforward search tool with well-documented parameters, the description is largely complete: an agent can decide when to use it and how to invoke it. The main gap is that no output shape is described, but the result of a search is natural enough that this is not a blocking omission.

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?

Schema description coverage is 100 percent, so the input schema already documents term, perType, and itemTypes with examples and defaults. The description contributes extra context about fields and intended use but largely repeats what the schema already expresses.

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 uses a specific verb and a specific resource: it performs a cross-type search over multiple Aras item types and enumerates the textual fields and types searched. This clearly distinguishes it from item-specific tools like aras_get_item or aras_query_items.

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 explicitly says to use this tool when you do not know which item type contains the term, and explains that Aras lacks a global search. It does not explicitly name alternative search tools for when the type is known, but that condition is strongly implied.

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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