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storefront-mcp

storefront-mcp

by cloudcart
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introspect_graphql_schema

Looks up CloudCart Storefront GraphQL types, queries, and mutations by name to find schema definitions and flag fields that only return data when the merchant runs the backing app.

Instructions

Look up types, queries and mutations in the CloudCart Storefront schema by name.

Use this when you already know what something is called. When you know what you want to do but not what it is called, read learn_cloudcart_storefront's guide first — it names the operation for each step.

It searches the names of types, queries and mutations, not of fields: look up the type that holds a field.

Results flag fields that only answer when the merchant runs the app behind them, which is the usual explanation for an empty list.

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": {
      "query": "<query>",
      "conversationId": "<conversationId>"
    },
    "name": "introspect_graphql_schema"
  }
}

Input Schema

NameRequiredDescriptionDefault
apiNoWhich schema to search.storefront
modeNo`full` expands the best match with all its fields. `compact` returns the summary line only — use it when you already have the signature and just want a sanity check.full
queryYesName or part of a name — 'Cart', 'cartLinesAdd', 'delivery', 'MoneyV2'.
filterNoRestrict the search to one category.
conversationIdYesFrom learn_cloudcart_storefront.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.3.1
    • removedInput schema / additionalProperties
      Removed value: -false
  2. First observedv0.3.0

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations, the description carries the burden and does disclose real behavioral traits: the search index covers type/query/mutation names but not field names, and results flag merchant-gated fields, which explains empty lists. It does not state that this is a pure read or describe response shape beyond that hint, so a small gap remains.

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?

Three short paragraphs, front-loaded with the core action, then routing, then a caveat about empty results. Each sentence carries information, though the merchant-gated-fields note is slightly oblique and could be tighter.

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?

No output schema exists, so the description must hint at return behavior; it does so partially by explaining that results flag merchant-gated fields and why a list may be empty. The full-vs-compact result difference is covered by the schema rather than the description, which is acceptable.

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%, so baseline is 3, but the description adds genuine meaning beyond the schema by clarifying what the `query` string actually matches (names of types/queries/mutations, not fields) — a distinction the schema's example list alone does not convey. It says nothing extra about `mode` or `filter`, which the schema already covers well.

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 ("Look up types, queries and mutations in the CloudCart Storefront schema by name") and immediately delimits scope against its sibling learn_cloudcart_storefront. An agent can distinguish this from the other two tools without opening any schema.

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

Usage Guidelines5/5

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

Gives an explicit when-to-use condition ("when you already know what something is called") and an explicit when-not with the named alternative (use learn_cloudcart_storefront when you know the goal but not the name). It also names the anti-pattern — searching for field names instead of the type that holds the field.

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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