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jackdark425

Financial Modeling Prep (FMP) MCP Server

by jackdark425

get_sp500_constituents

Retrieve the current list of S&P 500 companies for financial analysis and market tracking.

Instructions

Get list of S&P 500 index constituents

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The get_sp500_constituents tool is registered and implemented within the registerMarketTools function in src/tools/market.ts. It fetches data from the '/sp500-constituent' endpoint.
    server.registerTool(
      'get_sp500_constituents',
      {
        description: 'Get list of S&P 500 index constituents',
        inputSchema: z.object({}),
      },
      async () => {
        try {
          const data = await fetchFMP('/sp500-constituent');
          return jsonResponse(data);
        } catch (error) {
          return errorResponse(error);
        }
      }
    );
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 but offers minimal information. It doesn't specify if this is a read-only operation, how frequently the data updates, potential rate limits, authentication needs, or what format the list returns (e.g., symbols, names, weights). This leaves critical behavioral traits undocumented.

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's front-loaded with the core action and resource, making it easy to parse quickly. Every word earns its place by directly conveying the tool's purpose without redundancy or fluff.

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 the complexity of financial data tools and the lack of annotations or output schema, the description is incomplete. It doesn't explain what the output contains (e.g., list format, timestamps, metadata), how current the data is, or any limitations. For a tool in a server with many financial siblings, more context is needed to ensure proper use.

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 tool has 0 parameters, and the input schema has 100% description coverage (though empty). The description doesn't need to explain parameters, and it appropriately doesn't mention any. A baseline of 4 is applied since no parameters exist, and the description doesn't introduce confusion about inputs.

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 with a specific verb ('Get') and resource ('list of S&P 500 index constituents'), making it immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'search_symbol' or 'get_company_profile' that might also provide stock-related data, preventing a perfect score.

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 is provided on when to use this tool versus alternatives. For example, it doesn't clarify if this is for current constituents only, how it differs from 'search_symbol' for finding S&P 500 stocks, or whether it's suitable for historical data. The description lacks any context about usage scenarios 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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