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massive-com

Polygon-io MCP Server

Official

list_stock_financials

Retrieve fundamental financial data for companies by ticker, CIK, or company name. Filter by filing date, period of report, and other parameters to access detailed financial insights.

Instructions

Get fundamental financial data for companies.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cikNo
company_nameNo
company_name_searchNo
filing_dateNo
filing_date_gtNo
filing_date_gteNo
filing_date_ltNo
filing_date_lteNo
include_sourcesNo
limitNo
orderNo
paramsNo
period_of_report_dateNo
period_of_report_date_gtNo
period_of_report_date_gteNo
period_of_report_date_ltNo
period_of_report_date_lteNo
sicNo
sortNo
tickerNo
timeframeNo
Behavior1/5

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

No annotations are provided, so the description carries full burden for behavioral disclosure. It fails to describe any behavioral traits: it doesn't indicate if this is a read-only operation, what permissions might be required, rate limits, pagination behavior (despite a 'limit' parameter), or what the response format looks like. The description is too minimal to guide an agent on how the tool behaves.

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

Conciseness5/5

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

The description is extremely concise with a single sentence: 'Get fundamental financial data for companies.' It's front-loaded and wastes no words, though this brevity comes at the cost of completeness. Every word earns its place in conveying the core purpose.

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

Completeness1/5

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

Given the complexity (21 parameters, no annotations, no output schema), the description is completely inadequate. It doesn't explain what data is returned, how to interpret parameters, behavioral constraints, or how this tool fits among siblings. For a tool with rich filtering capabilities and no structured documentation, this minimal description leaves critical gaps.

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

Parameters1/5

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

The input schema has 21 parameters with 0% description coverage, and the tool description adds no parameter semantics. It doesn't explain what any parameter does (e.g., 'cik', 'ticker', 'filing_date'), how they interact, or which are required versus optional. With such low schema coverage, the description fails to compensate, leaving parameters completely undocumented.

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

Purpose3/5

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

The description states the tool 'Get fundamental financial data for companies', which provides a general purpose (verb+resource) but is vague about scope and format. It doesn't specify what 'fundamental financial data' includes (e.g., balance sheets, income statements) or distinguish it from sibling tools like 'get_ticker_details' or 'list_tickers' that might provide related financial information.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives. With many sibling tools available (e.g., 'list_tickers', 'get_ticker_details', 'list_dividends'), the description offers no context about when this specific tool is appropriate, what data it returns compared to others, or any prerequisites for use.

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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