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 tool 'estimates' value using an API, implying a read-only operation, but does not detail behavioral traits like rate limits, authentication needs, error handling, or output format. The description lacks context on what the estimation entails beyond high-level concepts.

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, consisting of two sentences that directly state the tool's purpose and method. There is no wasted text, and it efficiently communicates the core functionality without unnecessary elaboration, making it easy to parse.

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 (financial valuation), lack of annotations, and no output schema, the description is insufficient. It does not explain the return values, accuracy, limitations, or how the DCF calculation is performed, leaving gaps for an AI agent to understand the tool's full context and usage 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, with one parameter 'symbol' documented as 'Stock symbol.' The description does not add any semantic details beyond this, such as format examples or constraints. With high schema coverage, the baseline score is 3, as the schema adequately covers parameter meaning without extra description input.

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: 'Estimate the intrinsic value of a company' using the 'FMP Discounted Cash Flow Valuation API' based on 'expected future cash flows and discount rates.' It specifies the verb ('Estimate'), resource ('intrinsic value of a company'), and method (DCF valuation), but does not explicitly differentiate from sibling tools like 'calculateCustomDCF' or 'getLeveredDCFValuation' beyond mentioning the API source.

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 API but does not specify scenarios, prerequisites, or exclusions, such as comparing it to sibling tools like 'calculateCustomDCF' or 'getLeveredDCFValuation' for different DCF calculations. Usage is implied only by the tool's name and description context.

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