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Shopify MCP Server

Shopify MCP Server

by hamzashahbaz
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

shopify_sales_summary

Retrieve sales metrics including total sales, orders, AOV, returns, and discounts for specified date ranges to analyze store performance.

Instructions

Get a summary of sales metrics (total sales, net sales, orders, AOV, returns, discounts) for a date range. Defaults to last 30 days.

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_sales_summary"
  }
}

Input Schema

NameRequiredDescriptionDefault
sinceNoStart date in ShopifyQL format. Examples: '-30d', '-3m', '-1y', '2025-01-01'
untilNoEnd date in ShopifyQL format. Examples: 'today', '2025-12-31'
compareNoIf true, includes year-over-year comparison

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.6/5.0
Behavior2/5

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

With no annotations provided, the description carries full burden but only mentions the default date range behavior. It doesn't disclose important behavioral traits like whether this requires authentication, rate limits, what happens with invalid dates, or the format/structure of the returned summary. For a read operation with no annotation coverage, this leaves significant gaps.

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 concise sentences that are front-loaded with the core purpose followed by the default behavior. Every word earns its place with no redundancy or unnecessary elaboration.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with 3 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain what the summary output looks like, how metrics are calculated, whether data is real-time or cached, or any error conditions. The agent would struggle to use this effectively without trial and error.

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 fully documents all three parameters. The description adds minimal value beyond the schema by implying date range filtering but doesn't provide additional context about parameter interactions or semantics. Baseline 3 is appropriate when the schema does the heavy lifting.

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 verb 'Get' and the resource 'summary of sales metrics' with specific metrics listed (total sales, net sales, orders, AOV, returns, discounts). It distinguishes from siblings like shopify_sales_by_channel or shopify_sales_by_product by focusing on aggregated metrics rather than breakdowns.

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 provides clear context for when to use this tool ('for a date range' with 'Defaults to last 30 days'), which helps differentiate it from tools like shopify_sales_over_time or shopify_custom_query. However, it doesn't explicitly state when NOT to use it or name specific alternatives among siblings.

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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