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 and data types but does not cover critical aspects like rate limits, authentication requirements, error handling, or response format. For a tool with no annotation coverage, this is a significant gap in transparency about operational 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 front-loaded, stating the main purpose in the first sentence and elaborating with key data points. It avoids unnecessary details, but could be slightly more structured by explicitly separating usage context from data examples. Overall, it is efficient with minimal waste.

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's complexity (fetching financial data), lack of annotations, and no output schema, the description is incomplete. It does not explain the return format, potential errors, or how to interpret the data, which is crucial for an AI agent to use the tool effectively. The description should compensate for these gaps but falls short.

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 'symbol' parameter documented as 'Stock symbol'. The description adds context by implying the symbol is used to fetch company data, but it does not provide additional semantics beyond what the schema already states, such as format examples or validation rules. With high schema coverage, a 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: 'Access detailed company profile data' with a specific resource ('company profile data') and verb ('access'), and it lists key data points like market capitalization and stock price. However, it does not explicitly differentiate from sibling tools like 'getCompanyProfileByCIK' or 'getCompanyProfilesBulk', which might serve similar purposes with different inputs or scopes, so it lacks sibling differentiation.

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, such as other company profile tools in the sibling list (e.g., 'getCompanyProfileByCIK' for CIK-based access or 'getCompanyProfilesBulk' for batch processing). It mentions the API but does not specify prerequisites, exclusions, or contextual triggers, leaving usage unclear.

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