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 the tool 'provides post-debt company valuation' and 'offers investors a more accurate measure,' but lacks details on rate limits, authentication needs, error handling, or output format. For a valuation tool with zero annotation coverage, this is a significant gap in transparency.

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 two sentences long and efficiently conveys the tool's purpose and value proposition without unnecessary details. It is front-loaded with the main action and avoids redundancy, though it could be slightly more structured for clarity.

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 valuation, no annotations, and no output schema, the description is insufficient. It explains the tool's purpose but lacks critical details like output format, error conditions, or integration context, leaving gaps for an AI agent to understand how to interpret results or handle failures.

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' documented as 'Stock symbol.' The description does not add any parameter-specific information beyond what the schema provides, such as format examples or constraints. 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: 'Analyze a company's value with the FMP Levered Discounted Cash Flow (DCF) API, which incorporates the impact of debt.' It specifies the verb ('analyze'), resource ('company's value'), and method ('levered DCF'), but does not explicitly differentiate from sibling tools like 'getDCFValuation' (which likely provides unlevered DCF) or 'calculateCustomLeveredDCF' (which may allow custom inputs).

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 tool's purpose but does not specify scenarios, prerequisites, or exclusions, nor does it reference sibling tools like 'getDCFValuation' or 'calculateCustomLeveredDCF' for comparison. Usage is implied only by the tool's name and description.

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