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 accesses data via an API and is for tracking and analysis, implying a read-only operation, but does not specify details like rate limits, authentication requirements, data freshness, or pagination. For a tool with no annotations, this leaves significant gaps in understanding its 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, with two sentences that efficiently convey the tool's purpose and scope. There is no wasted language, and it directly addresses what the tool does without unnecessary elaboration.

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 accessing historical industry performance data, no annotations, and no output schema, the description is incomplete. It lacks details on behavioral traits (e.g., data sources, limitations), output format, or error handling, making it insufficient for an agent to fully understand how to use the tool 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, so the schema already documents all parameters (industry, from, to, exchange) with clear descriptions. The description adds no additional meaning or context beyond what the schema provides, such as example values or constraints, but the high schema coverage justifies a baseline score of 3.

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 historical performance data for industries' and 'Track long-term trends and analyze how different industries have evolved over time across various stock exchanges.' It specifies the verb ('access', 'track', 'analyze') and resource ('historical performance data for industries'), but does not explicitly differentiate it from sibling tools like 'getHistoricalSectorPerformance' or 'getIndustryPerformanceSnapshot'.

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 analyzing 'long-term trends' and 'evolved over time', but does not specify prerequisites, exclusions, or direct comparisons to sibling tools such as 'getHistoricalSectorPerformance' or 'getIndustryPerformanceSnapshot' for context-specific usage.

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