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mcp-shopify

mcp-shopify

by cloud9-labs
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

shopify_count_products

Count products in a Shopify store using optional vendor and product type filters to get accurate totals for inventory management and reporting.

Instructions

Count products with optional filters.

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": "shopify_count_products"
  }
}

Input Schema

NameRequiredDescriptionDefault
vendorNo
product_typeNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3/5.0
Behavior3/5

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

With no annotations, the description carries the burden of behavioral disclosure. 'Count products' communicates a non-mutating aggregate operation, but it does not explain return shape, filtering behavior, or whether both filters combine. This is minimal but not misleading.

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?

The description is a single direct sentence with no wasted words. It front-loads the operation, though it is perhaps too terse to fully support an agent making a correct call.

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?

This is a simple tool with two optional filters and no output schema, so the description is close to minimally viable. However, it lacks key context such as how filters apply, what the response contains, and how this differs from list_products, leaving meaningful gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It only says 'optional filters,' which adds little beyond the raw property names vendor and product_type. No detail is given about matching semantics, allowed values, or how the filters interact.

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 states a clear verb and resource: count products. It also mentions optional filters, which distinguishes it from list_products in intent, though it does not explicitly name any sibling tool.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives no guidance on when to use this tool instead of shopify_list_products or other siblings. It implies use for counting, but there is no explicit when-to-use or when-not-to-use context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server

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