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 mentions the API source and data types but lacks critical behavioral details: whether this is a read-only operation, any rate limits, authentication requirements, error handling, or pagination. For a search tool with zero annotation coverage, this leaves significant gaps in understanding how the tool behaves.

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. The second sentence adds useful detail about the data returned. There's no wasted text, but it could be slightly more structured (e.g., separating usage notes from data details) for a perfect score.

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 lack of annotations and output schema, the description is incomplete. It doesn't explain the return format, error conditions, or operational constraints. For a tool that interacts with an external API and returns potentially sensitive financial/political data, more context about reliability, data freshness, and limitations is needed to be fully helpful to an AI agent.

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 'name' documented as 'Senator name (first or last name)'. The description adds no additional parameter semantics beyond what the schema provides, such as format examples, search behavior (partial vs. exact match), or case sensitivity. With high schema coverage, the baseline score of 3 is appropriate.

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: 'Search for Senate trading activity by Senator name' with the specific resource 'FMP Senate Trades by Name API'. It mentions the type of data returned (trade dates, assets, amounts, conflicts of interest). However, it doesn't explicitly differentiate from sibling tools like 'getSenateTrades' or 'getHouseTradesByName', which would be needed for 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.

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 sibling tools like 'getSenateTrades' (which might search differently) or 'searchInsiderTradesByReportingName' (which could overlap). There's no context about prerequisites, limitations, or typical use cases beyond the basic search functionality.

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