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 filtering to 'identify the best opportunities' but lacks critical details: whether this is a read-only operation, if there are rate limits, authentication requirements, pagination behavior, or what the output format looks like (especially since there's no output schema). For a tool with 19 parameters and no annotations, 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 efficiently structured in two sentences: the first states the purpose and API source, the second lists key filter examples. It's front-loaded with the core function and avoids unnecessary details. However, it could be slightly more concise by integrating the filter examples more seamlessly.

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 (19 parameters, no annotations, no output schema), the description is incomplete. It doesn't explain the return format, pagination, error handling, or behavioral traits like rate limits. For a screening tool with many inputs and no structured output info, more context is needed to guide 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 description lists example filter criteria (market cap, price, volume, beta, sector, country) which aligns with the input schema parameters. Since schema description coverage is 100%, the schema already documents all 19 parameters thoroughly. The description adds minimal value beyond what's in the schema, meeting the baseline of 3 for high coverage without compensating for gaps.

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: 'Discover stocks that align with your investment strategy' using filtering criteria. It specifies the verb ('discover'), resource ('stocks'), and scope ('using the FMP Stock Screener API'). However, it doesn't explicitly differentiate from sibling tools like 'getActivelyTradingList' or 'searchCompaniesBySymbol', which might offer alternative ways to find stocks.

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 for stock discovery (e.g., 'getActivelyTradingList', 'searchCompaniesBySymbol'), there's no mention of when this screening approach is preferred, nor any prerequisites or exclusions. It merely states what the tool does without contextual usage advice.

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