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jackdark425

Financial Modeling Prep (FMP) MCP Server

by jackdark425

get_institutional_holders

Retrieve institutional ownership data from 13F filings for a specific stock ticker symbol to analyze investor holdings.

Instructions

Get institutional ownership (13F filings) for a stock

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolYesStock ticker symbol
limitNoNumber of holders to return (default: 100)

Implementation Reference

  • The handler function for 'get_institutional_holders' which fetches institutional ownership data from FMP API.
    server.registerTool(
      'get_institutional_holders',
      {
        description: 'Get institutional ownership (13F filings) for a stock',
        inputSchema: InstitutionalHoldersSchema,
      },
      async (args: z.infer<typeof InstitutionalHoldersSchema>) => {
        try {
          const limit = args.limit || 100;
          const data = await fetchFMP<InstitutionalHolder[]>(
            `/institutional-ownership/latest?symbol=${args.symbol.toUpperCase()}&limit=${limit}`
          );
          return jsonResponse(data);
        } catch (error) {
          return errorResponse(error);
        }
      }
    );
  • The Zod schema defining the inputs for the institutional holders tool.
    const InstitutionalHoldersSchema = z.object({
      symbol: SymbolSchema.describe('Stock ticker symbol'),
      limit: LimitSchema.describe('Number of holders to return (default: 100)'),
    });
  • Registration of 'get_institutional_holders' within registerAnalysisTools.
    server.registerTool(
      'get_institutional_holders',
      {
        description: 'Get institutional ownership (13F filings) for a stock',
        inputSchema: InstitutionalHoldersSchema,
      },
      async (args: z.infer<typeof InstitutionalHoldersSchema>) => {
        try {
          const limit = args.limit || 100;
          const data = await fetchFMP<InstitutionalHolder[]>(
            `/institutional-ownership/latest?symbol=${args.symbol.toUpperCase()}&limit=${limit}`
          );
          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. It mentions '13F filings' which hints at regulatory data sources, but fails to describe key traits like rate limits, authentication needs, data freshness, or response format (e.g., list of holders with details). This leaves significant gaps for a tool that likely involves external data fetching.

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 ('Get institutional ownership') and includes a clarifying detail ('13F filings') that adds value without verbosity, making it highly concise and well-structured.

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 tool's complexity (financial data fetching with parameters), lack of annotations, and no output schema, the description is incomplete. It doesn't address behavioral aspects like data sources, limitations, or return values, which are critical for effective use. The high schema coverage helps with parameters but doesn't compensate for other gaps.

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 input schema fully documents both parameters ('symbol' and 'limit'). The description adds no additional meaning beyond what's in the schema, such as format examples for 'symbol' or context for 'limit' (e.g., typical ranges). This meets 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 action ('Get') and resource ('institutional ownership (13F filings) for a stock'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_insider_trading' or 'get_balance_sheet', which also provide financial data but for different aspects, so it doesn't reach the highest 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?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, timing considerations (e.g., based on filing dates), or comparisons to siblings like 'get_insider_trading' for different ownership data, leaving usage context implied at best.

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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