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 full burden. It mentions the API source and general purpose but lacks critical behavioral details: whether this is a read-only operation, rate limits, authentication requirements, pagination, error handling, or what the output format looks like. For a data retrieval tool with no annotation coverage, this is insufficient.

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 efficiently structured in two sentences: the first states the core functionality, and the second adds context about granularity and use case. It's front-loaded with the main purpose and avoids unnecessary fluff, though it could be slightly more concise by integrating the use case into the first sentence.

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?

For a data retrieval tool with no annotations and no output schema, the description is incomplete. It doesn't cover behavioral aspects like safety, performance, or output format, which are crucial for an AI agent to use it correctly. The description adequately states what it does but fails to provide enough context for reliable invocation.

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 all three parameters (symbol, from, to). The description adds no additional parameter semantics beyond what's in the schema—it doesn't explain format constraints, valid symbol examples beyond ^GSPC, or date range limitations. Baseline 3 is appropriate when schema does all the work.

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 1-minute interval intraday data for stock indexes' with specific resource (stock indexes) and granularity (1-minute). It distinguishes from siblings like getIndex1HourData and getIndex5MinuteData by specifying the time interval, but doesn't explicitly contrast with other index data tools beyond the name.

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 implies usage for tracking short-term price movements and trading volume, suggesting when this granular data might be useful. However, it doesn't provide explicit guidance on when to choose this tool over alternatives like getIndex1HourData or getIndex5MinuteData, nor does it mention any prerequisites or exclusions.

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