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shopify-multi-store

by alex-brecher
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TypeScript
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Run a Shopify Report

shopify_report
Read-onlyIdempotent

Run read-only reports across selected Shopify stores to compare inventory, prices, catalog, orders, customers, and analytics, with per-store results and completeness indicators.

Instructions

Run one read-only report across selected stores; each store returns its own result and completeness indicators. Reports:

  • portfolio_snapshot: Shop identity and product, order, customer and location counts. stores optional (all stores).

  • store_locations: Active, inactive, legacy, fulfillment, inventory and address status of locations. stores optional (all stores).

  • compare_inventory: Inventory, price, status and catalog details for exact SKUs. Needs skus (1-50).

  • compare_prices: Price and compare-at price for exact SKUs, with mismatches and missing variants. Needs skus (1-50).

  • get_product_everywhere: One exact SKU or handle across stores. Needs identifier and matchBy (sku or handle).

  • compare_catalog: Titles, status, vendor, type and inventory for exact product handles. Needs handles (1-50).

  • compare_collections: Titles, sort order, product counts, SEO and images for exact collection handles. Needs handles (1-50).

  • catalog_gap_report: Products missing or with different status across stores. first: products scanned per store (default 250).

  • catalog_health: Missing vendor, type, SEO, media, alt text, and active products without inventory. first (default 100).

  • duplicate_sku_report: SKUs repeated inside a store and shared across stores. first: variants scanned per store (default 250).

  • low_stock_report: Active variants at or below threshold (default 10), separating low, zero and negative.

  • recent_product_changes: Products updated in the last days (default 7). first (default 100).

  • list_unfulfilled_orders: Recent open unfulfilled orders. days (default 7), first (default 25).

  • fulfillment_sla_report: Open unfulfilled orders by age bucket and SLA breaches. lookbackDays (default 90), slaDays (default 2), first (default 100).

  • order_summary: Order values, discounts, shipping, tax, cancellations and statuses; currencies separate. days (default 30), first (default 100).

  • customer_growth: New customers in the current and previous period of days (default 30).

  • analytics: Run one ShopifyQL query on each store and return columns, rows and a chart hint. Needs query and read_reports.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNoLookback or period length in days.
skusNocompare_inventory, compare_prices: exact SKUs.
firstNoRows per store; each report has its own default and maximum.
queryNoanalytics: a ShopifyQL query.
reportYesWhich report to run. See the tool description for each report's inputs.
storesNoStore aliases. Optional only for portfolio_snapshot and store_locations (then every store).
handlesNocompare_catalog, compare_collections: exact handles.
matchByNoget_product_everywhere: whether identifier is a SKU or a handle.
slaDaysNofulfillment_sla_report: age after which the SLA is breached.
thresholdNolow_stock_report: maximum aggregate quantity to include.
identifierNoget_product_everywhere: the exact SKU or product handle.
lookbackDaysNofulfillment_sla_report: how far back to look.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv2.0.1

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint/idempotentHint/destructiveHint, so the safety profile is covered. The description adds genuine behavioral context beyond that: per-store fan-out ('each store returns its own result') and 'completeness indicators', which tells the agent results may be partial across stores. It omits rate limits and error/partial-failure behavior.

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?

Front-loaded with the tool's purpose, then a scannable per-report bullet list. The length is justified by 17 enum values, though some lines restate schema-level facts; still, every bullet carries selection-relevant information.

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?

Given a 12-parameter, 17-mode tool with no output schema, the description is nearly complete: it covers report selection, required inputs, and partial-result behavior. What's missing is a clearer statement of the return shape per report (it only hints at 'columns, rows and a chart hint' for analytics).

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

Parameters4/5

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

Schema coverage is 100% (baseline 3), but the description adds meaningful value the schema lacks: it assigns each of the 12 parameters to the specific reports that consume them and supplies defaults the schema does not state (threshold default 10, days default 7, first defaults per report). This goes beyond the structured fields.

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?

States a specific verb and resource ('Run one read-only report across selected stores') and enumerates the 17 selectable report values with their scope, which distinguishes it immediately from siblings like shopify_search, shopify_get, and shopify_graphql_query.

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?

Each report line states the inputs it needs ('Needs skus (1-50)', 'stores optional (all stores)', 'Needs query and read_reports'), which effectively routes the agent to the correct report value. It does not, however, say when to prefer this tool over shopify_search or shopify_graphql_query for overlapping data, so it stops short of explicit alternatives.

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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