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Financial Modeling Prep MCP Server

Financial Modeling Prep MCP Server

by imbenrabi
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

getCompanyExecutives

Read-onlyIdempotent

Retrieve key company executives by stock symbol, including names, titles, compensation, gender, and birth year for governance and financial analysis.

Instructions

Retrieve detailed information on company executives with the FMP Company Executives API. This API provides essential data about key executives, including their name, title, compensation, and other demographic details such as gender and year of birth.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "symbol": "<symbol>"
    },
    "name": "getCompanyExecutives"
  }
}

Input Schema

NameRequiredDescriptionDefault
activeNoFilter for active executives
symbolYesStock symbol

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv2.9.0
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
    • removedInput schema / additionalProperties
      Removed value: -false
  2. First observed

TDQS

B3.1/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true and openWorldHint=true, so the safety profile is covered. The description adds value by disclosing the payload contents (title, compensation, demographics), but says nothing about coverage limits, whether inactive or historical executives are included, or result ordering.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences with the core purpose front-loaded, but the second sentence spends words on vendor branding ('with the FMP Company Executives API. This API provides...') and a loose 'other demographic details' catch-all rather than tightening the field list.

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?

For a two-parameter read-only lookup with no output schema, the description does the minimum: it sketches the returned fields. It omits the required symbol input, the active-executive filter, and any indication of response shape or whether multiple executives are returned, which an agent would need to plan a call.

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 both parameters are documented in the schema and the baseline of 3 applies. The description adds no meaning beyond it — notably it never mentions the 'active' filter, which is the one parameter whose accepted values (string, no enum) an agent could get wrong.

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?

States a specific verb and resource ('Retrieve detailed information on company executives') and enumerates the returned fields (name, title, compensation, gender, year of birth). It is clearly distinct from the nearest siblings in spirit, but it never names them (e.g., getExecutiveCompensation, getCompanyProfile) so the differentiation is implicit rather than explicit.

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?

There is no when-to-use guidance at all: nothing says to use this for a roster of executives versus getExecutiveCompensation for pay data or getCompanyProfile for general company facts. Nor does it mention that a stock symbol is required or what the 'active' filter is for, leaving the agent to infer both selection and prerequisites.

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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