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eliaskress

FlowCheck Financial API MCP Server

by eliaskress

Connect Shopify

flowcheck_connect_shopify

Connect a Shopify store to automatically sync orders and payouts for financial workflow analysis and validation.

Instructions

Connect a Shopify store. Orders and payouts will sync automatically. The access token must have read access to Orders and Payouts. FlowCheck encrypts it with AES-256-GCM.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
shopYesShopify store domain (e.g. my-store.myshopify.com)
access_tokenYesShopify access token (shpat_...)

Implementation Reference

  • The registration and handler implementation for the `flowcheck_connect_shopify` tool. It validates the input `shop` and `access_token` and makes a POST request to the `/connect/shopify` endpoint via the client.
    server.registerTool(
      "flowcheck_connect_shopify",
      {
        title: "Connect Shopify",
        description:
          "Connect a Shopify store. Orders and payouts will sync automatically. " +
          "The access token must have read access to Orders and Payouts. " +
          "FlowCheck encrypts it with AES-256-GCM.",
        inputSchema: z.object({
          shop: z
            .string()
            .describe("Shopify store domain (e.g. my-store.myshopify.com)"),
          access_token: z
            .string()
            .describe("Shopify access token (shpat_...)"),
        }),
      },
      async ({ shop, access_token }) => {
        const result = await client.request("POST", "/connect/shopify", {
          body: { shop, access_token },
        });
        return { content: [{ type: "text" as const, text: result }] };
      },
    );
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. It discloses key behavioral traits: automatic syncing of orders and payouts, encryption of the access token with AES-256-GCM, and the required token permissions. This covers operational aspects and security practices, though it could add more on error handling or rate limits.

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 concise and front-loaded, with three sentences that each add value: stating the action and outcome, specifying token requirements, and noting encryption. There is no wasted text, and it efficiently communicates essential 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 no annotations and no output schema, the description does well by covering the tool's purpose, behavior, and prerequisites. However, it lacks details on return values (e.g., success confirmation or error responses) and could mention potential side effects or limitations, leaving minor gaps in completeness.

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 schema fully documents the parameters (shop domain and access token). The description adds minimal semantics beyond the schema, such as specifying the token must have 'read access to Orders and Payouts', but this is marginal. Baseline 3 is appropriate as the schema does the heavy lifting.

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 the specific action ('Connect a Shopify store') and resource ('Shopify store'), and distinguishes it from siblings like 'flowcheck_connect_stripe' by specifying the platform. It includes the outcome ('Orders and payouts will sync automatically'), making the purpose explicit and distinct.

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?

The description implies usage for connecting a Shopify store, but does not explicitly state when to use this tool versus alternatives (e.g., other 'connect' tools like Stripe) or provide exclusions. It mentions prerequisites ('access token must have read access to Orders and Payouts'), which offers some context, but lacks clear comparative guidance.

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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