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polygon-mcp

polygon-mcp

by atomcp-ai
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

stocks_get_snapshot_all

Retrieve real-time snapshot data for all or specified stock symbols, including quotes and market information.

Instructions

Get snapshots for all or specified stock symbols.

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": "stocks_get_snapshot_all"
  }
}

Input Schema

NameRequiredDescriptionDefault
symbolsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden for behavioral disclosure but only says 'Get snapshots.' It does not mention return format, handling of invalid symbols, what data is included in a snapshot, or any side effects or limitations, leaving significant behavioral ambiguity.

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 sentence of eight words, immediately front-loading the core function with no filler or redundancy. It is extremely concise while conveying the essential purpose.

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

Completeness2/5

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

Despite the tool having only one parameter, the lack of an output schema, annotations, and any description of return values or edge cases makes the description insufficient for a snapshot tool that likely returns complex data. Important context such as response structure and potential errors is completely absent.

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

Parameters3/5

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

The description explains the key semantics of the 'symbols' parameter: 'all' or 'specified', which suggests null/omitted means all and a list means specified. However, it does not specify the symbol format (e.g., ticker strings) or the behavior for empty arrays, and schema coverage is 0%, so the description only partially compensates.

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

Purpose4/5

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

The description clearly states the action ('Get snapshots') and the resource ('stock symbols'), with explicit scope ('all or specified') that differentiates it from the singular stocks_get_snapshot. However, it does not explicitly contrast with sibling tools or clarify what a snapshot contains.

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

Usage Guidelines3/5

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

The phrase 'all or specified' implies this tool is for batch snapshots, but there is no explicit statement of when to use it versus alternatives like stocks_get_snapshot. The usage context is inferred rather than directly addressed.

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

Deploy Server

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