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 accessing data via an API but doesn't specify whether this is a read-only operation, if it requires authentication, rate limits, or potential costs. The description lists data fields returned but doesn't describe the format (e.g., JSON array, time series), pagination, or error handling. For a data-fetching tool with no annotation coverage, this leaves significant gaps in understanding its 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 efficiently structured in two sentences: the first states the core purpose and API, and the second lists the data insights provided. It's front-loaded with the main action and avoids unnecessary fluff. However, the list of data fields (e.g., 'open, high, low, close prices...') is somewhat verbose and could be streamlined without losing clarity.

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 (fetching financial data with three parameters), lack of annotations, and no output schema, the description is moderately complete. It specifies the data returned but doesn't cover behavioral aspects like error cases, rate limits, or data freshness. The absence of an output schema means the description should ideally hint at the response structure, which it partially does by listing fields. However, it falls short of providing a full picture for safe and effective use 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 clear documentation for 'symbol', 'from', and 'to' parameters. The description adds no additional parameter semantics beyond what's in the schema—it doesn't explain date format constraints, symbol validation, or optional vs. required usage. Given the high schema coverage, the baseline score of 3 is appropriate, as the schema does the heavy lifting without description enhancement.

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 full price and volume data for any stock symbol' using a specific API (FMP Comprehensive Stock Price and Volume Data API). It specifies the data types returned (open, high, low, close prices, trading volume, etc.), making the verb+resource relationship explicit. However, it doesn't differentiate from sibling tools like 'getLightChart' or 'getUnadjustedChart', which likely provide similar but different data scopes.

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. With many sibling tools like 'getLightChart', 'getUnadjustedChart', and 'getQuote', there's no indication of what makes this tool unique or when it should be preferred. The description mentions 'full price and volume data' but doesn't clarify if this implies historical data, real-time data, or how it differs from other chart/data tools in the list.

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