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 and historical' data and the API source, but fails to disclose critical behavioral traits such as rate limits, authentication requirements, data freshness, error handling, or response format. For a data-fetching 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 concise and well-structured in two sentences: the first states the purpose and scope, and the second provides a generic use case. It is front-loaded with key information, though the second sentence could be more specific to earn a higher 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 complexity of fetching economic data, no annotations, and no output schema, the description is incomplete. It lacks details on behavioral aspects (e.g., rate limits, auth), response structure, error cases, and differentiation from siblings. For a tool with 3 parameters and no structured output information, more context is needed to adequately guide 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 clear documentation for 'name', 'from', and 'to' parameters. The description adds minimal value beyond the schema by implying the tool handles economic indicators (e.g., GDP, unemployment) but does not provide additional semantics like valid indicator names, date format details, or default behaviors. Baseline 3 is appropriate as the schema does the heavy lifting.

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 and historical economic data for key indicators like GDP, unemployment, and inflation with the FMP Economic Indicators API.' It specifies the verb ('access'), resource ('economic data'), and scope ('real-time and historical'), though it doesn't explicitly differentiate from sibling tools like 'getEconomicCalendar' or 'getTreasuryRates' that might also provide economic data.

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 minimal usage guidance, stating 'Use this data to measure economic performance and identify growth trends,' which is a generic use case rather than specific when-to-use instructions. It does not mention when to choose this tool over alternatives like 'getEconomicCalendar' or 'getTreasuryRates' from the sibling list, nor does it specify prerequisites or exclusions.

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