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eliaskress

FlowCheck Financial API MCP Server

by eliaskress

List Discrepancies

flowcheck_list_discrepancies

Identify and filter open financial discrepancies including missing deposits, amount mismatches, and timing alerts to monitor transaction integrity.

Instructions

List open discrepancies: missing bank deposits, amount mismatches, and timing alerts. Filter by status and type.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusNoFilter by discrepancy status
typeNoFilter by discrepancy type
limitNoResults per page (default 50, max 100)
cursorNoPagination cursor from previous response

Implementation Reference

  • The handler function that executes the 'flowcheck_list_discrepancies' tool logic by calling the FlowCheck client.
    async (params) => {
      const result = await client.request("GET", "/discrepancies", { params });
      return { content: [{ type: "text" as const, text: result }] };
    },
  • Input schema definition for the 'flowcheck_list_discrepancies' tool using Zod.
    inputSchema: z.object({
      status: z
        .enum(["open", "resolved", "dismissed"])
        .optional()
        .describe("Filter by discrepancy status"),
      type: z
        .enum(["missing_deposit", "amount_mismatch", "timing"])
        .optional()
        .describe("Filter by discrepancy type"),
      limit: z
        .number()
        .min(1)
        .max(100)
        .optional()
        .describe("Results per page (default 50, max 100)"),
      cursor: z
        .string()
        .optional()
        .describe("Pagination cursor from previous response"),
    }),
  • Registration of the 'flowcheck_list_discrepancies' tool within the MCP server.
    server.registerTool(
      "flowcheck_list_discrepancies",
      {
        title: "List Discrepancies",
        description:
          "List open discrepancies: missing bank deposits, amount mismatches, " +
          "and timing alerts. Filter by status and type.",
        inputSchema: z.object({
          status: z
            .enum(["open", "resolved", "dismissed"])
            .optional()
            .describe("Filter by discrepancy status"),
          type: z
            .enum(["missing_deposit", "amount_mismatch", "timing"])
            .optional()
            .describe("Filter by discrepancy type"),
          limit: z
            .number()
            .min(1)
            .max(100)
            .optional()
            .describe("Results per page (default 50, max 100)"),
          cursor: z
            .string()
            .optional()
            .describe("Pagination cursor from previous response"),
        }),
      },
      async (params) => {
        const result = await client.request("GET", "/discrepancies", { params });
        return { content: [{ type: "text" as const, text: result }] };
      },
    );
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'List open discrepancies' and filtering, but doesn't cover critical aspects like whether this is a read-only operation, pagination behavior (implied by cursor but not explained), rate limits, authentication needs, or what the response format looks like. It provides basic action but lacks operational details.

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 a single, efficient sentence that front-loads the core purpose ('List open discrepancies') and includes key details (examples and filtering). Every word contributes value with zero waste, making it appropriately sized and well-structured.

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?

Given no annotations and no output schema, the description is incomplete for a tool with four parameters and list functionality. It covers the basic purpose and filtering but omits behavioral context (e.g., pagination, response format) and usage guidelines versus siblings. It's minimally adequate but has clear gaps in operational transparency.

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 all four parameters. The description adds minimal value beyond the schema by mentioning 'Filter by status and type,' which aligns with the schema's enum descriptions. No additional parameter semantics are provided, meeting the baseline for high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'List open discrepancies' with specific examples (missing bank deposits, amount mismatches, timing alerts). It distinguishes itself from siblings like flowcheck_get_alerts or flowcheck_get_reconciliation by focusing specifically on discrepancies, though it doesn't explicitly contrast with those tools.

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 context through 'Filter by status and type,' suggesting when to apply parameters. However, it lacks explicit guidance on when to use this tool versus alternatives like flowcheck_get_alerts or flowcheck_get_reconciliation, and doesn't mention prerequisites or exclusions.

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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