Financial Modeling Prep MCP Server

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the API source (FMP Stock Batch Quote API) and the type of data returned (current prices, volume, detailed data), but doesn't disclose important behavioral aspects like rate limits, authentication requirements, error handling, or response format. The description adds some context but leaves significant gaps.

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 perfectly sized at two sentences with zero waste. The first sentence states the core functionality, and the second sentence explains the value proposition. Every word earns its place.

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?

For a read-only tool with no annotations and no output schema, the description provides adequate basic information about what the tool does and when to use it. However, it lacks details about the response structure, error conditions, and operational constraints that would be helpful for an AI agent. The description is complete enough for basic understanding but could be more comprehensive.

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?

Schema description coverage is 100%, so the schema already fully documents the single 'symbols' parameter. The description doesn't add any parameter-specific information beyond what's in the schema (comma-separated format). Baseline 3 is appropriate when the schema does the heavy lifting.

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 specific action ('Retrieve multiple real-time stock quotes'), resource ('with the FMP Stock Batch Quote API'), and scope ('in a single request'). It distinguishes itself from potential siblings like getQuote or getQuoteShort by emphasizing batch/multiple capability.

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 clear context for when to use this tool ('making it easier to track large portfolios or monitor multiple stocks simultaneously'), which implicitly suggests it's for bulk operations rather than single-stock queries. However, it doesn't explicitly name alternatives or state when NOT to use it.

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