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 states it 'retrieves' data, implying a read-only operation, and mentions 'comprehensive compensation data' and 'filing details and links to official documents,' which adds some context about the data scope. However, it lacks details on rate limits, authentication needs, error handling, or data freshness, which are critical 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.

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

The description is concise and front-loaded, stating the core purpose in the first sentence: 'Retrieve comprehensive compensation data for company executives with the FMP Executive Compensation API.' Additional details about data types and filing info are provided efficiently. It avoids redundancy and is appropriately sized for the tool's complexity.

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 tool has no annotations, no output schema, and a simple input schema with one parameter, the description is moderately complete. It covers the purpose and data scope but lacks behavioral details like rate limits or error handling. For a read-only tool with minimal structured data, it's adequate but has clear gaps in usage guidelines and transparency.

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, with the single parameter 'symbol' described as 'Stock symbol.' The description adds no additional parameter semantics beyond this, as it doesn't explain format constraints, examples, or how the symbol maps to executives. With high schema coverage, the baseline score of 3 is appropriate, as the schema already documents the parameter adequately.

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 comprehensive compensation data for company executives' with specific details like 'salaries, stock awards, total compensation, and other relevant financial data.' It distinguishes itself from siblings like 'getCompanyExecutives' (which likely provides general executive info) by focusing on compensation data. However, it doesn't explicitly differentiate from 'getExecutiveCompensationBenchmark,' which might be a closer sibling.

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 Executive Compensation API' but doesn't specify prerequisites, limitations, or when to choose this over other tools like 'getCompanyExecutives' or 'getExecutiveCompensationBenchmark.' There's no explicit when/when-not or alternative usage context.

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