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 'real-time' data and 'up-to-date financial data,' which implies freshness, but doesn't cover critical aspects like rate limits, authentication requirements, data format, error handling, or whether this is a read-only operation. For a financial data tool with no annotations, this is a significant gap.

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, with the core purpose stated in the first sentence. The second sentence adds value by highlighting use cases. There's no wasted text, though it could be slightly more structured (e.g., separating purpose from benefits).

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 data retrieval, no annotations, and no output schema, the description is incomplete. It lacks details on response format, data granularity, error cases, and operational constraints. While it states the purpose, it doesn't provide enough context for reliable tool invocation in a production setting.

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?

Schema description coverage is 100%, so the schema fully documents the three parameters (symbol, limit, period). The description doesn't add any parameter-specific details beyond what's in the schema, such as examples or constraints. This meets the baseline for high schema coverage, but doesn't enhance understanding.

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 real-time income statement data for public companies, private companies, and ETFs.' It specifies the verb ('access'), resource ('income statement data'), and scope ('public companies, private companies, and ETFs'), though it doesn't explicitly differentiate from sibling tools like getIncomeStatementAsReported or getIncomeStatementTTM, which prevents 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 mentions general use cases ('Track profitability, compare competitors, and identify business trends'), but provides no explicit guidance on when to use this tool versus alternatives. It doesn't reference sibling tools or specify prerequisites, leaving the agent to infer usage from context alone.

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