Financial Modeling Prep MCP Server

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It describes what data is retrieved but fails to mention critical behaviors: whether this is a read-only operation, if it requires authentication, rate limits, error handling, or the format of returned data. The mention of 'SEC documents for further verification' hints at external links but doesn't clarify tool behavior.

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

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

The description is concise and well-structured in two sentences: the first states the core purpose and data points, the second adds context about SEC links. It avoids unnecessary details and is front-loaded with key information. Minor verbosity in mentioning 'FMP Company Employee Count API' by name could be trimmed, but overall it's efficient.

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

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of financial data retrieval, lack of annotations, and no output schema, the description is incomplete. It omits behavioral traits (e.g., read-only status, error handling), does not explain the return structure (e.g., list format, fields beyond those mentioned), and provides no usage context relative to siblings. This leaves significant gaps for an AI agent to invoke the tool effectively.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage, clearly documenting 'symbol' as a stock symbol and 'limit' with default and max values. The description adds no parameter-specific semantics beyond what the schema provides, such as examples or constraints on symbol format. However, with high schema coverage, a baseline score of 3 is appropriate as the schema adequately covers parameter meanings.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Retrieve detailed workforce information for companies, including employee count, reporting period, and filing date.' It specifies the verb ('retrieve'), resource ('workforce information'), and key data points. However, it does not explicitly differentiate from sibling tools like 'getHistoricalEmployeeCount' or 'getCompanyProfile', which might also provide employee-related data, leaving room for ambiguity.

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

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 mentions the 'FMP Company Employee Count API' and links to SEC documents, but does not specify use cases, prerequisites, or exclusions. With many sibling tools available (e.g., 'getHistoricalEmployeeCount', 'getCompanyProfile'), the lack of comparative context is a significant gap.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.