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GlacianNex

stockdata-mcp

by GlacianNex

fmp_request

Query any FMP stable endpoint directly for data like ETF holdings, 13F filings, economic indicators, and SEC documents. Works as a fallback for endpoints without a dedicated tool.

Instructions

Call any FMP stable endpoint directly — an escape hatch for the ~250 endpoints without a dedicated tool here (ETF holdings, 13F, senate trades, economic indicators, SEC filings, transcripts, and so on).

Args: endpoint: Path after /stable/, e.g. "etf/holdings" or "treasury-rates". params: Query parameters, e.g. {"symbol": "SPY"}. The API key is added automatically.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsNo
endpointYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It mentions the API key is added automatically and that it's an escape hatch, but it does not disclose potential side effects, rate limits, error handling, or what happens when the endpoint is invalid. For a generic request tool, this is a significant gap.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise but includes a multi-line docstring with args. It front-loads the main purpose and then adds parameter notes. Some redundancy in the args block, but overall compact and readable.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With 2 parameters, a permissive schema, and an output schema present, the description is mostly adequate. It provides a broad list of use cases and parameter examples. However, it could mention response format or typical errors, but the output schema may cover return values. Given the generic nature, it is reasonably complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It explains the endpoint format with an example ('etf/holdings') and parameter format with example, plus notes the API key is auto-added. The params schema is permissive (additionalProperties), so examples are crucial. Two parameters well-documented via examples, though not exhaustive.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it calls any FMP stable endpoint as an escape hatch for the ~250 endpoints without a dedicated tool, listing examples. This distinguishes it from siblings which target specific endpoints like fmp_quote or fmp_earnings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explicitly frames the tool as an escape hatch for endpoints without a dedicated tool, implying when to use it (when no sibling matches). However, it does not explicitly say when NOT to use it, e.g., for endpoints that already have dedicated tools.

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

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