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 states the tool accesses data via an API and mentions its purpose for tracking changes over time, but it doesn't disclose critical behavioral traits such as whether it's read-only (implied but not explicit), rate limits, authentication needs, error handling, or the format of returned data. For a data-fetching 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 appropriately sized with two sentences that efficiently convey the tool's purpose and high-level utility. It's front-loaded with the core action ('Access historical market capitalization data') and avoids unnecessary details. However, the second sentence about 'enabling long-term assessments' could be slightly more precise, but overall, it's concise and well-structured 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 financial data tool with 4 parameters, no annotations, and no output schema, the description is incomplete. It lacks details on behavioral aspects (e.g., data freshness, API constraints), doesn't explain the return format or structure, and provides no usage guidelines relative to siblings. For a tool in a server with many similar financial tools, this description falls short of providing enough context for an AI agent to use it effectively without additional inference.

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 all parameters (symbol, limit, from, to). The description adds no additional parameter semantics beyond what the schema provides, such as explaining relationships between 'from' and 'to' or default behaviors. Since the schema does the heavy lifting, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.

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 historical market capitalization data for a company' with a specific verb ('access') and resource ('historical market capitalization data'), and mentions the API source. However, it doesn't explicitly differentiate from sibling tools like 'getMarketCap' or 'getBatchMarketCap', which appear to handle current or bulk market cap data, leaving some ambiguity about when to choose this specific historical tool.

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. It mentions 'enabling long-term assessments of a company's growth or decline,' which implies a use case but doesn't specify prerequisites, exclusions, or direct comparisons to sibling tools like 'getMarketCap' (likely for current data) or 'getBatchMarketCap' (likely for bulk data). This lack of explicit when-to-use or when-not-to-use guidance limits its utility for an AI agent.

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