Web Intel

Shopify Store Intelligence

shopify-store-intelligence

Read-only

Confirm a site runs on Shopify and pull store intelligence from its public feeds — product count, price range, top vendors/categories, newest listing and a rough revenue-band heuristic. No login, no Shopify API key. — $0.01/call, x402 (USDC on base).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "websites": "<websites>"
    },
    "name": "shopify-store-intelligence"
  }
}

Input Schema

Name	Required	Description	Default
`websites`	Yes	List of websites to check (e.g. `allbirds.com` or `https://example.com`). One row per site.
`maxConcurrency`	No	How many websites to check in parallel.

Schema Changelog

Changes observed during successful MCP inspections.

First observedJul 27, 2026

TDQS

A4.4/5.0

Behavior5/5

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

The description discloses important behavioral traits beyond annotations: uses public feeds (non-invasive), requires no authentication, costs $0.01/call (payment method), and mentions the 'rough revenue-band heuristic' indicating approximate results. This adds significant context to the readOnlyHint and destructiveHint annotations.

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?

The description is extremely concise, with two sentences that front-load the main action and outputs, followed by constraints (no login, cost). Every sentence adds value, and the structure is easy to parse.

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?

For a tool with 2 params and no output schema, the description lists expected outputs and key constraints, making it reasonably complete. However, it does not explain behavior for non-Shopify sites or the response format, leaving minor gaps.

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?

The input schema already provides detailed descriptions for both parameters (websites list and maxConcurrency). The description does not add parameter-specific semantics beyond restating the overall purpose, so the baseline 3 is appropriate since schema coverage is 100%.

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 uses specific verbs ('Confirm', 'pull') and clearly identifies the resource ('site runs on Shopify') and output types (product count, price range, top vendors/categories, newest listing, revenue-band heuristic). It distinguishes itself from sibling tools like tech-stack-detector by focusing on Shopify-specific intelligence.

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: it works on public feeds with no login/API key, implying low-friction usage for store intelligence. However, it does not explicitly mention when not to use it or name alternative tools, so it falls short of a full 5.

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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