mcp-server-woocommerce

get_product

Read-only

Fetch complete product details by ID, including description, tags, brands, and variations. Use the fields parameter to request only the needed fields.

Instructions

Get full details of a single product by ID. Returns more fields than list_products including description, tags, brands, and variations. Use fields param to request only needed fields.

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": {
      "id": "<id>"
    },
    "name": "get_product"
  }
}

Input Schema

Name	Required	Description	Default
`id`	Yes	Product ID
`fields`	No	Comma-separated fields to return (default: id,name,type,status,sku,price,regular_price,sale_price,stock_status,stock_quantity,categories,images,attributes,slug,description,short_description,manage_stock,weight,tags,default_attributes,variations)

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.2.0Aug 6, 2026

TDQS

A4/5.0

Behavior3/5

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

The annotations already declare readOnlyHint=true, so the agent knows it's a safe read. The description adds context about richer return data and the fields parameter but does not disclose additional behavioral traits like error handling or rate limits. This is acceptable for a simple read-only tool, so a mid-range score is appropriate.

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 sentences, direct and front-loaded, with no filler. Every word earns its place: it states the resource, the scope, what extra fields are returned, and how to optimize.

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 single-product retrieval with two parameters and no output schema, the description is sufficiently complete. It explains what the tool does, how it differs from list_products, and how to limit fields. Minor gaps like error responses are not critical for this simple tool.

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%, with both id and fields documented. The description adds no new semantic meaning beyond the schema; it merely reiterates that fields can be used to request only needed fields. Baseline of 3 applies since schema carries the parameter details.

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 clearly states the tool's purpose: 'Get full details of a single product by ID.' It uses a specific verb (get) and resource (product) and distinguishes itself from list_products by noting it returns more fields, including description, tags, brands, and variations.

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 implies when to use this tool by contrasting it with list_products ('Returns more fields than list_products') and provides usage guidance for the fields parameter. It lacks explicit exclusions or when-not-to-use scenarios, but the context is clear.

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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