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 is for 'retrieving' data, implying a read-only operation, but does not specify critical details such as rate limits, authentication requirements, data format, or potential constraints (e.g., maximum symbols per request). For a bulk data 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 tool's purpose, and the second provides usage context. It avoids unnecessary fluff and is front-loaded with key information. However, it could be slightly more efficient by integrating the user context more seamlessly, but overall, it earns its place with minimal waste.

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 a bulk data retrieval tool with no annotations and no output schema, the description is incomplete. It lacks details on behavioral traits (e.g., rate limits, authentication), output format, and error handling. While it covers purpose and basic usage, it does not compensate for the missing structured data, making it inadequate for safe and effective tool invocation by 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 the single parameter 'date' documented as 'Date in YYYY-MM-DD format.' The description does not add any additional meaning beyond this, such as explaining date range validity or default behaviors. Given the high schema coverage, a baseline score of 3 is appropriate, as the schema adequately handles parameter semantics 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: 'retrieve end-of-day stock price data for multiple symbols in bulk.' It specifies the verb ('retrieve'), resource ('end-of-day stock price data'), and scope ('multiple symbols in bulk'), which is specific and actionable. However, it does not explicitly differentiate from sibling tools like 'getQuote' or 'getBatchQuotes,' which might also retrieve price data, leaving some ambiguity in sibling context.

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 implied usage context by stating it's 'ideal for financial analysts, traders, and investors who need to assess valuations for a large number of companies,' suggesting use for bulk data needs. However, it lacks explicit guidance on when to use this tool versus alternatives (e.g., 'getQuote' for single symbols or 'getBatchQuotes' for real-time data), and does not mention prerequisites or exclusions, leaving room for interpretation.

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