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polygon-mcp

polygon-mcp

by atomcp-ai
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

reference_get_stock_dividends

Retrieve historical cash dividends for any stock using ticker and ex-dividend date filters. Access dividend payment records to analyze payout trends.

Instructions

Get historical cash dividends for stocks.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "reference_get_stock_dividends"
  }
}

Input Schema

NameRequiredDescriptionDefault
sortNopay_date
limitNo
orderNoasc
tickerNo
ex_dividend_dateNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.8/5.0
Behavior2/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It only states the basic purpose and offers no additional context such as return format, filtering behavior, or limitations. It adds minimal value beyond the one-line summary.

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 a single, concise sentence with no redundant words. Every word contributes to the core purpose. It is appropriately front-loaded and efficient.

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?

The tool has 5 parameters, no annotations, and no output schema, yet the description provides only a terse summary. It fails to explain how to filter, what the response contains, or any usage nuances. This is severely incomplete for effective tool selection and invocation.

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?

Schema description coverage is 0%, and the description does not compensate by explaining any parameters. The five parameters (ticker, ex_dividend_date, sort, limit, order) are left entirely to the schema, which has no descriptions. The description adds no meaning beyond the raw schema.

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 the tool's function: 'Get historical cash dividends for stocks.' It specifies a precise verb ('Get'), a specific resource ('historical cash dividends'), and the asset class ('stocks'). This distinguishes it from siblings like reference_get_stock_splits and reference_get_stock_financials.

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?

The description provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites, when to choose dividends over splits or financials, or any context for use. This is a clear gap.

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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