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jackdark425

Financial Modeling Prep (FMP) MCP Server

by jackdark425

get_quote

Retrieve real-time stock price data for any ticker symbol to monitor current market values and support investment decisions.

Instructions

Get real-time stock quote for a symbol (e.g., AAPL, TSLA, MSFT)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolYesStock ticker symbol (e.g., AAPL)

Implementation Reference

  • The 'get_quote' tool is registered within registerMarketTools, defining its schema, description, and handler function.
    // Get Quote
    server.registerTool(
      'get_quote',
      {
        description: 'Get real-time stock quote for a symbol (e.g., AAPL, TSLA, MSFT)',
        inputSchema: QuoteSchema,
      },
      async (args: z.infer<typeof QuoteSchema>) => {
        try {
          const data = await fetchFMP<StockQuote[]>(`/quote?symbol=${args.symbol.toUpperCase()}`);
          return jsonResponse(data);
        } catch (error) {
          return errorResponse(error);
        }
      }
    );
  • The handler function that executes the 'get_quote' tool logic by fetching data from FMP API.
    async (args: z.infer<typeof QuoteSchema>) => {
      try {
        const data = await fetchFMP<StockQuote[]>(`/quote?symbol=${args.symbol.toUpperCase()}`);
        return jsonResponse(data);
      } catch (error) {
        return errorResponse(error);
      }
    }
  • The input schema validation for the 'get_quote' tool.
    const QuoteSchema = z.object({
      symbol: z.string().describe('Stock ticker symbol (e.g., AAPL)'),
    });
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 mentions 'real-time' which adds context about data freshness, but fails to disclose other behavioral traits such as rate limits, authentication needs, error handling, or what the return format looks like (e.g., price, volume). This is a significant gap for a tool with no annotation coverage.

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 waste, front-loaded with the core purpose and examples. It is appropriately sized for a simple tool with one parameter, making it easy to scan and understand quickly.

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 the tool's low complexity (1 parameter, no nested objects) and high schema coverage, the description is adequate but incomplete. It lacks output details (no output schema provided) and behavioral context like error cases or data sources, which could hinder an agent's ability to use it correctly in varied scenarios.

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?

The input schema has 100% description coverage, with the parameter 'symbol' well-documented in the schema. The description adds value by providing examples (AAPL, TSLA, MSFT) that clarify the expected format beyond the schema's generic description, though it doesn't detail constraints like symbol validity or case sensitivity.

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 ('Get real-time stock quote') and resource ('for a symbol'), with examples (AAPL, TSLA, MSFT) that help distinguish it from sibling tools like get_historical_chart or get_company_profile, which serve different financial data purposes.

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 real-time quotes, but does not explicitly state when to use this tool versus alternatives like get_historical_chart for historical data or search_symbol for symbol lookup. No exclusions or prerequisites are mentioned, leaving some ambiguity in context.

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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