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. It mentions 'real-time' data and 'quick snapshots', implying low latency, but fails to disclose critical behavioral traits such as rate limits, authentication requirements, error handling, or data freshness guarantees. For a tool with no annotation coverage, 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, stating the core purpose in the first sentence. Both sentences add value by specifying the API source ('FMP Stock Quote Short API') and example data fields. There is no wasted verbiage, though it could be slightly more structured with bullet points for the data examples.

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 lack of annotations and output schema, the description is incomplete. It doesn't explain the return format, error conditions, or performance characteristics. For a tool that provides financial data, this omission is significant, as the agent cannot anticipate the structure or reliability of the response without additional context.

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 'symbol' documented as 'Stock symbol'. The description adds no additional semantic context beyond this, such as format examples (e.g., 'AAPL' for Apple) or validation rules. With high schema coverage, the baseline score of 3 is appropriate as the description doesn't compensate but doesn't detract either.

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: 'Get quick snapshots of real-time stock quotes' with specific data examples like 'current price, volume, and price changes'. It distinguishes itself from siblings like 'getQuote' by emphasizing 'quick snapshots' and 'short' in the name, though it doesn't explicitly compare to other quote tools like 'getBatchQuotesShort'.

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 guidance on when to use this tool, mentioning 'instant market insights' but not specifying when to choose it over alternatives like 'getQuote' or 'getBatchQuotesShort'. No exclusions or prerequisites are stated, leaving the agent with little context for tool selection among siblings.

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