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HasData

com.hasdata/shopify

shopify_collections: GET /

hasdata_shopify_collections_getCollections

List collections from any public Shopify storefront with pagination, returning IDs, titles, handles, images, and timestamps. Use handles to explore category-specific products or track merchandising changes.

Instructions

Get Shopify Store Collections

Lists collections from any public Shopify storefront URL with limit (up to 250) and page pagination. Returns each collection's id, title, handle, body_html description, image, and timestamps. Use the returned handles as input to the Shopify Products endpoint to enumerate category-specific catalogs, or to map a competitor's merchandising taxonomy and track collection changes over time.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesThe URL of the Shopify store. For example, 'https://b2bdemoexperience.myshopify.com'.
pageNoThe page number of the results to retrieve. Must be a positive integer.
limitNoThe maximum number of collections to retrieve. Must be between 1 and 250.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.0.0

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden and does well: it discloses the public-storefront scope, pagination behavior, limit cap of 250, and the specific returned fields. It doesn't mention rate limits or error behavior, but the core behavioral expectations are clear.

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 concise and front-loaded, stating the main function first and then adding return-detail and usage context. The closing sentence about tracking collection changes is slightly extra but still adds practical context.

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 no output schema and no annotations, the description adequately compensates by explaining return fields, pagination, and the public URL requirement. It stops short of covering defaults or error scenarios, but the information needed to invoke the tool correctly 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 100%, so the baseline is 3. The description adds only marginal reinforcement by mentioning 'limit (up to 250) and page pagination,' which the schema already documents. It does not introduce new semantic details beyond the schema.

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 'Lists collections from any public Shopify storefront URL' with a specific verb, resource, and scope. It also lists the returned fields and distinguishes collections from the sibling products endpoint by referring to it as a separate input consumer.

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?

It gives clear context: use this to fetch collection-level data from public Shopify stores and feed handles into the Shopify Products endpoint. It doesn't explicitly say when not to use it, but the workflow guidance makes the intended usage obvious.

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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