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Octopart

by io.github.pipeworx-io
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Octopart Multi Match

octopart_multi_match
Read-onlyIdempotent

Batch-match a list of manufacturer part numbers in one call — ideal for BOM (bill of materials) enrichment. Each query resolves to the best-matching part(s) with distributor offers. Example: octopart_multi_match({ mpns: ["SY89832UMG", "SY89874UMG"], limit: 1, _apiKey: "client_id:client_secret" })

Example tool call

This call uses example arguments supplied in the tool’s input schema.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "mpns": [
        "SY89832UMG",
        "GRM188R71C104KA01D"
      ],
      "limit": 1,
      "_apiKey": "your-octopart-client_id:your-octopart-client_secret"
    },
    "name": "octopart_multi_match"
  }
}

Input Schema

NameRequiredDescriptionDefault
mpnsYesList of manufacturer part numbers to match (exact-match), e.g. ["SY89832UMG", "GRM188R71C104KA01D"]
limitNoMax parts to return per MPN (default 1)
_apiKeyYesNexar OAuth2 credentials as "client_id:client_secret". Get one at https://portal.nexar.com
countryNoISO country code for pricing/availability context, e.g. "US" (optional)
currencyNoISO currency code for converted prices, e.g. "USD" (optional)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already cover the safety profile (readOnlyHint, idempotentHint, openWorldHint, destructiveHint=false), lowering the bar. The description adds useful context that each query 'resolves to the best-matching part(s) with distributor offers' and that one call handles many MPNs, but it does not disclose rate limits, quota consumption, or behavior for unmatched part numbers. Some value added, but not rich behavioral disclosure.

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 purpose-driven sentences plus a compact working example, with the core purpose front-loaded. The example is helpful but partially redundant with the two examples already in the input schema, so it is not maximally economical.

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?

The schema is rich (100% coverage, examples, auth guidance) and annotations cover safety, but with no output schema the description's responsibility for return behavior is higher. It states parts and distributor offers are returned, but omits failure handling for unmatched MPNs and response-size/limit concerns for a batch-oriented tool. Adequate but with clear gaps.

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%, so the schema already fully documents all five parameters with examples and defaults. The description's inline example mirrors the schema examples and adds no new parameter semantics beyond what the structured data provides. Baseline 3 is appropriate.

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 resource ('Batch-match a list of manufacturer part numbers in one call') and frames the use case ('ideal for BOM enrichment'). The 'batch' framing clearly distinguishes it from siblings octopart_part (single) and octopart_search (search).

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 gives a clear context for when to use the tool ('ideal for BOM enrichment', a list of MPNs in one call) and what each query does. However, it never names the alternatives (octopart_part, octopart_search) or states when not to use this tool, so the routing guidance is implied rather than explicit.

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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