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ClawyPro

Clawy MCP Server

by ClawyPro

fmp_financial

Retrieve financial statements (income, balance sheet, cash flow) for companies using stock ticker symbols to analyze financial performance.

Instructions

Get company financial statements (income statement, balance sheet, cash flow) from FMP.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolYesStock ticker symbol
statementYesType of financial statement
periodNoReporting period (default: annual)
limitNoNumber of periods to return (default 5)

Implementation Reference

  • src/tools/fmp.ts:16-27 (registration)
    The "fmp_financial" tool is registered here in the fmpTools array, specifying its input schema and API endpoint.
    {
      name: "fmp_financial",
      description: "Get company financial statements (income statement, balance sheet, cash flow) from FMP.",
      inputSchema: z.object({
        symbol: z.string().describe("Stock ticker symbol"),
        statement: z.enum(["income-statement", "balance-sheet-statement", "cash-flow-statement"])
          .describe("Type of financial statement"),
        period: z.enum(["annual", "quarter"]).optional().describe("Reporting period (default: annual)"),
        limit: z.number().optional().describe("Number of periods to return (default 5)"),
      }),
      endpoint: "/v1/fmp/financial",
    },
  • The handler logic for "fmp_financial" (and all other tools in allTools) is dynamically registered in src/index.ts. It uses the `gatewayRequest` helper to fetch data from the API endpoint defined in the tool registration.
    // Register all tools
    for (const tool of allTools) {
      server.tool(
        tool.name,
        tool.description,
        tool.inputSchema.shape,
        async (params) => {
          const method = tool.method || "POST";
          const result = await gatewayRequest(method, tool.endpoint, params as Record<string, unknown>);
    
          if (result.error) {
            return {
              content: [{ type: "text" as const, text: `Error (${result.status}): ${result.error}` }],
              isError: true,
            };
          }
    
          const text = typeof result.data === "string"
            ? result.data
            : JSON.stringify(result.data, null, 2);
    
          return {
            content: [{ type: "text" as const, text }],
          };
        },
      );
Behavior2/5

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

No annotations are provided, so the description carries full burden. It states what data is retrieved but doesn't disclose behavioral traits like authentication requirements, rate limits, error conditions, data freshness, or response format. The description is minimal and lacks operational context needed for effective use.

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 with zero wasted words. It front-loads the core purpose and includes key details (statement types and source) without unnecessary elaboration. Every word earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

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 4 parameters. It doesn't explain what the tool returns (e.g., data format, structure), error handling, or operational constraints. For a financial data retrieval tool, this leaves significant gaps in understanding how to use it effectively.

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%, providing clear documentation for all parameters. The description adds no parameter-specific information beyond what's in the schema (e.g., it doesn't explain relationships between parameters or provide examples). Baseline 3 is appropriate since the schema does the heavy lifting.

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 action ('Get') and resource ('company financial statements') with specific types listed (income statement, balance sheet, cash flow) and source ('from FMP'). It distinguishes from siblings like fmp_quote (which likely provides price quotes) but doesn't explicitly contrast with other financial data tools like finnhub_query or dart_financial.

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

Usage Guidelines2/5

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

No guidance on when to use this tool versus alternatives is provided. The description doesn't mention when this tool is appropriate compared to other financial data tools (e.g., finnhub_query, dart_financial) or general search tools. Usage is implied by the tool name and description but not explicitly stated.

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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