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 describes the tool as providing a 'comprehensive snapshot' and lists key metrics, but does not address important behavioral aspects such as data source (e.g., SEC filings), update frequency, rate limits, authentication requirements, or error handling. For a tool with no annotations, this leaves significant gaps in understanding its operational context.

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 a single, well-structured sentence that efficiently conveys the tool's purpose and key metrics. It is front-loaded with the main function and avoids unnecessary details. However, it could be slightly more concise by omitting redundant phrasing like 'comprehensive snapshot' if 'key metrics' already implies detail, but overall it is appropriately sized with zero 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 financial data and the lack of annotations and output schema, the description is incomplete. It does not explain the return format (e.g., JSON structure), data granularity (e.g., time series or single point), or potential limitations (e.g., data availability for certain symbols or periods). For a tool with three required parameters and no output schema, more context is needed to ensure 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', 'year', and 'quarter'. The description adds no additional parameter semantics beyond what the schema provides, such as format examples (e.g., symbol format like 'AAPL') or constraints (e.g., valid year ranges). With high schema coverage, the baseline score of 3 is appropriate, as the description does not compensate but also does not 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: to provide a comprehensive snapshot of institutional holdings for a specific stock symbol, tracking metrics like investor count, share changes, investment value, and ownership percentages over time. It specifies the verb ('provides') and resource ('institutional holdings'), but does not explicitly differentiate from sibling tools like 'getHolderPerformanceSummary' or 'getETFHoldersBulk', which might offer overlapping or related data.

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 does not mention prerequisites, such as requiring a valid stock symbol, year, and quarter, or suggest other tools for different types of holdings data (e.g., 'getETFHoldersBulk' for ETF holdings). Usage is implied only through the description of what the tool does, without explicit context or exclusions.

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