Financial Modeling Prep MCP Server

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool is for search and retrieval, implying a read-only operation, but doesn't clarify authentication requirements, rate limits, error handling, or response format. This is inadequate for a tool with three parameters and no output schema, as critical behavioral traits are omitted.

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 a single, efficient sentence that front-loads the core purpose ('Search and retrieve industry classification details') and includes relevant details (resources, API source). There's no wasted verbiage, though it could be slightly more structured to highlight key distinctions from sibling tools.

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 (three parameters, no annotations, no output schema), the description is insufficiently complete. It lacks guidance on usage, behavioral traits like response format or error handling, and doesn't compensate for the absence of structured metadata. This leaves significant gaps for an AI agent to effectively invoke the tool.

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, clearly documenting each parameter (symbol, cik, sicCode). The description adds no additional semantic context beyond what the schema provides, such as parameter relationships or search logic. Since the schema does the heavy lifting, the baseline score of 3 is appropriate, though the description doesn't enhance parameter 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: 'Search and retrieve industry classification details for companies' with specific resources mentioned (SIC codes, industry titles, business information). It distinguishes itself from sibling tools like 'getAllIndustryClassification' by emphasizing search functionality rather than bulk retrieval, though the distinction could be more explicit.

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 like 'getAllIndustryClassification' or 'searchCompaniesBySymbol'. It mentions the API source (FMP Industry Classification Search API) but doesn't specify use cases, prerequisites, or exclusions, leaving the agent with minimal contextual direction.

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