Skip to main content
Glama

Polygon Io

by io.github.pipeworx-io

Aggregates

aggregates
Read-onlyIdempotent

Massive (formerly Polygon.io) OHLC price bars for a US stock ticker — 1 minute through quarterly granularity. Returns timestamped open/high/low/close + volume + VWAP. Use for charting equities, intraday analysis, backtesting historical prices.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toYes
fromYes
sortNo
limitNo
tickerYes
adjustedNo
timespanYes
multiplierYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countNoNumber of results
statusNoAPI response status
tickerNoTicker symbol
resultsNoOHLC bar data
adjustedNoWhether data is adjusted
next_urlNoNext page URL if available
field_legendNoLegend for the single-letter OHLC bar keys (o/h/l/c/v/vw/n/t).

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed2 schema fields changed
    • addedOutput schema / properties / field_legend
      Added value: +{
+  "description": "Legend for the single-letter OHLC bar keys (o/h/l/c/v/vw/n/t).",
+  "type": "object"
+}
    • addedOutput schema / properties / results / items / properties / date
      Added value: +{
+  "description": "Bar start as an ISO 8601 timestamp (derived from `t`).",
+  "type": "string"
+}
  2. Changed2 schema fields changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "from": "2024-01-01",
+    "multiplier": 1,
+    "ticker": "AAPL",
+    "timespan": "day",
+    "to": "2024-01-31"
+  },
+  {
+    "from": "2024-01-15",
+    "limit": 100,
+    "multiplier": 15,
+    "ticker": "TSLA",
+    "timespan": "minute",
+    "to": "2024-01-16"
+  }
+]
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "adjusted": {
+      "description": "Whether data is adjusted",
+      "type": "boolean"
+    },
+    "count": {
+      "description": "Number of results",
+      "type": "number"
+    },
+    "next_url": {
+      "description": "Next page URL if available",
+      "type": "string"
+    },
+    "results": {
+      "description": "OHLC bar data",
+      "items": {
+        "properties": {
+          "c": {
+            "description": "Close price",
+            "type": "number"
+          },
+          "h": {
+            "description": "High price",
+            "type": "number"
+          },
+          "l": {
+            "description": "Low price",
+            "type": "number"
+          },
+          "n": {
+            "description": "Number of transactions",
+            "type": "number"
+          },
+          "o": {
+            "description": "Open price",
+            "type": "number"
+          },
+          "t": {
+            "description": "Timestamp",
+            "type": "number"
+          },
+          "v": {
+            "description": "Volume",
+            "type": "number"
+          },
+          "vw": {
+            "description": "Volume weighted average",
+            "type": "number"
+          }
+        },
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "status": {
+      "description": "API response status",
+      "type": "string"
+    },
+    "ticker": {
+      "description": "Ticker symbol",
+      "type": "string"
+    }
+  },
+  "type": "object"
+}
  3. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the description does not need to state safety. It adds value by detailing the granularity range and return fields, which is behavioral context beyond the annotations. No contradictions found.

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 two sentences, front-loaded with the primary purpose and followed by use cases. Every word contributes information, with no fluff or repetition of schema fields.

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

Completeness3/5

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

Given the tool's complexity (8 parameters, 5 required) and no schema descriptions, the description provides a solid overview but does not fully cover all parameter semantics. Since an output schema exists, return values are not needed, but the input handling is incomplete (e.g., 'adjusted' and 'sort' are undocumented). It is adequate but leaves some gaps.

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?

Schema description coverage is 0%, so the description must explain parameters. It mentions timespan granularity and ticker, and examples in the schema clarify date format, but parameters like 'adjusted', 'sort', and 'limit' are not explained. The description partially compensates but leaves gaps for several of the 8 parameters.

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 provides OHLC price bars with granularity from 1 minute to quarterly, and lists return fields (open/high/low/close, volume, VWAP). It also gives specific use cases (charting, intraday analysis, backtesting), distinguishing it from siblings like daily_open_close or grouped_daily.

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?

The description explicitly suggests when to use the tool (charting, intraday analysis, backtesting) but does not mention alternatives or when not to use it. It implies contexts but lacks explicit exclusions or comparisons to sibling tools, so it's clear but not fully comprehensive.

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

All Polygon Io toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

B3.2/5.0
Disambiguation3/5

Tools like ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded have overlapping purposes (all answer questions via a universal router), with only subtle distinctions (beta version, grounded mode). Additionally, many tools like entity_profile, compare_entities, recent_changes, and resolve_entity all pull SEC/company data, and polymarket_arbitrage, polymarket_edges, polymarket_fill_risk, bet_research all relate to prediction markets, creating potential confusion. However, each tool does have a somewhat distinct purpose and detailed descriptions help differentiate them, so it's not extreme overlap.

Naming Consistency2/5

Tool names are mostly lowercase with underscores (e.g., 'ask_pipeworx', 'compare_entities', 'resolve_entity'), but there's a mix of verb-first (bulk_splits, list_subscriptions) and noun-first (data_types, get_quote) patterns. Also 'aggregates' and 'grouped_daily' both fetch bars but have different naming styles. The naming is inconsistent with no clear uniform pattern, and some names are vague like 'helpers' or 'utility-*'.

Tool Count2/5

43 tools is quite heavy for a single MCP server, exceeding the typical 15-25 range for 'too many'. While the server aggregates many different domains (Polygon stocks, Pipeworx data, Polymarket, npm, etc.), the sheer number makes it overwhelming for an agent to discover and select the right tool. Many tools are meta-tools (ask_pipeworx, discover_tools) that add complexity rather than mapping to a clear domain.

Completeness4/5

The server covers a huge range of operations: stock data (retrieve, search, details), prediction markets (arbitrage, edges, research, fill risk), entity resolution, subscriptions, memory, and meta-tools. There are some gaps like no obvious tool for modifying stock data (not expected) and the Polymarket side lacks a tool for placing actual trades or managing positions. But overall the surface is quite complete for a comprehensive data/research server.

Resources