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HasData

hasdata-mcp

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shopify_products: GET /

hasdata_shopify_products_getProducts

Retrieve products from any public Shopify store. Optionally filter by collection, control pagination and limit to get product details like prices, SKUs, and inventory status for competitive analysis or catalog building.

Instructions

Get Shopify Store Products

Pulls products from any public Shopify storefront URL, optionally filtered by a collection handle, with limit (up to 250) and page pagination. Returns product id, title, handle, vendor, product_type, tags, body_html, images, variants with prices/SKUs/inventory status, and timestamps. Use for competitive price monitoring, catalog mirroring, availability tracking, building product datasets for comparison shopping, or feeding structured SKU data into downstream analytics and dropshipping pipelines.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesThe URL of the Shopify store. For example, 'https://b2bdemoexperience.myshopify.com'.
limitNoThe maximum number of products to retrieve. Must be between 1 and 250.
pageNoThe page number of the results to retrieve. Must be a positive integer.
collectionNoThe handle of the collection to filter the products. Provide the collection handle as a string.
Behavior3/5

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

Describes read-only data pulling and pagination, but lacks details on rate limits, authentication requirements for public stores, or error handling. Annotations are absent so description carries full burden.

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 clear action and resource. Use cases are listed but in prose; could be more structured but remains efficient.

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?

Covers purpose, parameters, and use cases, but omits details on pagination looping, error scenarios, and potential restrictions. Adequate but not fully comprehensive.

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 covers all parameters, description adds context like 'public' URL and limit up to 250, reinforcing schema descriptions.

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?

Clearly states it retrieves products from a Shopify store, listing specific return fields and distinguishing it from sibling collection tool.

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

Usage Guidelines3/5

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

Lists use cases but does not explicitly compare to alternatives or state when not to use this tool. Implicitly differentiated from collections tool.

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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