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. While it mentions accessing detailed information about recent share issuances, it does not cover critical aspects like whether this is a read-only operation, rate limits, authentication requirements, response format, or pagination behavior. The description is insufficient for a search tool with no annotation coverage.

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 concise and front-loaded, consisting of two sentences that directly state the tool's purpose and value. There is no wasted language, though it could be slightly more structured by separating functional description from benefits.

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 lack of annotations and output schema, the description is incomplete. It does not explain what the search returns (e.g., list of offerings, fields included), error conditions, or limitations. For a search tool with no structured behavioral data, this leaves significant gaps for an AI agent to understand how to use it effectively.

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 the single parameter 'name' clearly documented as 'Company name or stock symbol to search for'. The description adds no additional parameter semantics beyond what the schema provides, such as search behavior, case sensitivity, or partial matching rules, so it meets the baseline for high schema coverage.

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 searches for equity offerings by company name or stock symbol using the FMP Equity Offering Search API, providing detailed information about recent share issuances. It specifies the verb ('search'), resource ('equity offerings'), and scope ('by company name or stock symbol'), but does not explicitly differentiate from sibling tools like 'getLatestEquityOfferings' or 'getEquityOfferingsByCIK'.

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 staying informed on company fundraising activities, but does not specify use cases, prerequisites, or exclusions compared to other equity offering-related tools in the sibling list.

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