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CommerceWeave MCP

CommerceWeave MCP

by mysterekkk
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

Find a product by SKU, EAN or name

commerce_find_product
Read-onlyIdempotent

Locate the same product across Allegro, Base.com and WooCommerce by SKU, EAN or name. Returns candidate matches to verify before using as a write target.

Instructions

Looks for the same product on several platforms by SKU, EAN or name. SKU matches are exact; name search is a substring match. Matches are candidates only: SKUs may be missing or reused, so confirm identity before using a result as a write target.

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": "commerce_find_product"
  }
}

Input Schema

NameRequiredDescriptionDefault
eanNo
skuNo
queryNo
connectionIdsNoConnection ids to include (see commerce_list_connections). Omit for all connections.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnly, idempotent, non-destructive and open-world, so the safety profile is covered. The description adds genuinely useful behavior beyond that: exact SKU matching vs substring name matching, and the risk that SKUs may be missing or reused. It does not describe result shape, per-platform aggregation, or how multiple supplied identifiers are combined.

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?

Three compact sentences, front-loaded with the operation and followed by matching semantics and the candidate caveat. No filler, though the caveat sentence could be tightened.

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 no output schema, the description should say what comes back; it gestures at per-platform candidates but not the result shape. Identifier combination rules are also unstated. Still, for a four-parameter read-only lookup the essential decision information is present.

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 only 25%, so compensation is expected. The description adds matching semantics for sku (exact) and query (substring), which is real value, but says nothing about ean or how ean/sku/query/connectionIds interact when several are provided; only connectionIds carries a schema description.

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 (looks for) and resource (the same product) with explicit scope: several platforms, matched by SKU, EAN or name. The cross-platform, candidate-result nature of the operation is clear enough to separate it from a plain list/search products tool, though no sibling is named.

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?

Gives concrete usage context: results are candidates and must be identity-confirmed before use as a write target, which is a real when-to-use/when-not-to-trust boundary. It stops short of naming an alternative tool for browsing or full listing.

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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