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Glama

Polygon Io

by io.github.pipeworx-io

Dividends

dividends
Read-onlyIdempotent

Historical and upcoming cash + stock dividends for a US-listed ticker, from Massive (formerly Polygon.io): ex-date, record date, pay date, declaration date, cash amount, dividend type, frequency. Use for income analysis and dividend-capture strategies.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
tickerNo
ex_dividend_dateNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countNoNumber of results
statusNoAPI response status
resultsNoDividends data
next_urlNoNext page URL if available

Schema Changelog

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

  1. Changed2 schema fields changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "limit": 5,
+    "ticker": "KO"
+  }
+]
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "count": {
+      "description": "Number of results",
+      "type": "number"
+    },
+    "next_url": {
+      "description": "Next page URL if available",
+      "type": "string"
+    },
+    "results": {
+      "description": "Dividends data",
+      "items": {
+        "properties": {
+          "amount": {
+            "description": "Dividend amount",
+            "type": "number"
+          },
+          "currency": {
+            "description": "Currency",
+            "type": "string"
+          },
+          "declared_date": {
+            "description": "Declared date",
+            "type": "string"
+          },
+          "ex_dividend_date": {
+            "description": "Ex-dividend date",
+            "type": "string"
+          },
+          "payment_date": {
+            "description": "Payment date",
+            "type": "string"
+          },
+          "record_date": {
+            "description": "Record date",
+            "type": "string"
+          },
+          "ticker": {
+            "description": "Ticker symbol",
+            "type": "string"
+          }
+        },
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "status": {
+      "description": "API response status",
+      "type": "string"
+    }
+  },
+  "type": "object"
+}
  2. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior, so the description only needs to supplement. It adds context about the time scope ('historical and upcoming') and enumerates returned fields, providing useful behavioral detail beyond the annotations.

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 that front-loads the core purpose and lists key output fields, with no filler or repetition. It earns its place efficiently and is easy to parse at a glance.

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?

The tool has an output schema (present but not shown) and the description lists the return fields, so output context is adequate. However, the lack of parameter guidance and the absence of any mention of preconditions (e.g., valid ticker format) leaves the input side incomplete. The description is useful but not fully comprehensive for a tool with three undocumented parameters.

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%, yet the description fails to explain any parameter semantics. While 'for a US-listed ticker' hints at the ticker parameter, it does not clarify 'limit' or 'ex_dividend_date', leaving the agent without guidance on how to use these inputs effectively. Given the low coverage, the description should compensate but does not.

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 returns historical and upcoming cash and stock dividends for a US-listed ticker, with a specific list of data fields (ex-date, record date, pay date, declaration date, cash amount, dividend type, frequency). It distinguishes itself from sibling tools by being the only dividend-specific data source, and the mention of 'Massive (formerly Polygon.io)' adds source clarity.

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 recommends usage for 'income analysis and dividend-capture strategies,' providing a clear context. It does not explicitly mention when not to use or alternative tools, but given there are no dividend-specific siblings, this guidance is sufficient and not misleading.

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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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