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Polygon-io MCP Server

Polygon-io MCP Server

Official
by massive-com
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

get_aggs

Retrieve aggregate bars for a specific ticker within a defined date range and custom time window using specified parameters. Ideal for analyzing financial data trends over time.

Instructions

List aggregate bars for a ticker over a given date range in custom time window sizes.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "ticker": "<ticker>",
      "multiplier": "<multiplier>",
      "timespan": "<timespan>",
      "from_": "<from_>",
      "to": "<to>"
    },
    "name": "get_aggs"
  }
}

Input Schema

NameRequiredDescriptionDefault
adjustedNo
from_Yes
limitNo
multiplierYes
paramsNo
sortNo
tickerYes
timespanYes
toYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.8/5.0
Behavior2/5

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

No annotations are provided, so the description carries full burden. It mentions 'list' (implying read-only) and scope details, but lacks critical behavioral information: authentication requirements, rate limits, pagination (given 'limit' parameter), data freshness, error handling, or output format. For a 9-parameter tool with no annotation coverage, this is insufficient.

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?

Single sentence, front-loaded with core purpose, zero redundant words. Every element ('List aggregate bars', 'for a ticker', 'over a given date range', 'in custom time window sizes') contributes directly to understanding the tool's function.

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?

Given high complexity (9 parameters, 5 required), no annotations, no output schema, and 0% schema description coverage, the description is inadequate. It covers basic purpose but misses parameter explanations, behavioral context, output details, and sibling differentiation needed for effective tool use.

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

Parameters2/5

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 only vaguely references 'ticker', 'date range', and 'custom time window sizes' (hinting at 'multiplier' and 'timespan'), leaving 6 other parameters (adjusted, limit, params, sort, from_, to) completely unexplained. The description adds minimal value beyond the schema's parameter names.

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 ('List aggregate bars') and target resource ('for a ticker'), with additional scope details ('over a given date range in custom time window sizes'). It distinguishes from siblings like 'get_daily_open_close_agg' by specifying custom time windows, but doesn't explicitly contrast with 'list_aggs' or other aggregation tools.

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 explicit guidance on when to use this tool versus alternatives like 'get_daily_open_close_agg', 'get_grouped_daily_aggs', or 'list_aggs'. The description implies usage for time-series aggregation with custom windows but provides no context about prerequisites, limitations, or comparison to sibling 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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