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Polygon-io MCP Server

Official

list_trades

Retrieve and filter trades for a specific ticker symbol using the Polygon-io MCP Server. Query by timestamp, set limits, and sort results for precise trade data analysis.

Instructions

Get trades for a ticker symbol.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
orderNo
paramsNo
sortNo
tickerYes
timestampNo
timestamp_gtNo
timestamp_gteNo
timestamp_ltNo
timestamp_lteNo
Behavior1/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. The description only states 'Get trades for a ticker symbol,' which reveals nothing about the tool's behavior—such as whether it's a read-only operation, requires authentication, has rate limits, returns paginated results, or handles errors. This lack of information makes it impossible for an agent to understand how to interact with the tool safely and effectively.

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 extremely concise—a single sentence with no wasted words—and front-loaded with the core action. While this brevity contributes to clarity in structure, it comes at the cost of completeness, as noted in other dimensions. Every word in the description serves a purpose, making it structurally 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?

Given the complexity (10 parameters, 1 required), lack of annotations, 0% schema description coverage, and no output schema, the description is completely inadequate. It fails to explain the tool's behavior, parameter meanings, or return values, leaving critical gaps that prevent an agent from using the tool correctly. The description does not compensate for the missing structured information.

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?

The input schema has 10 parameters with 0% description coverage, meaning none of the parameters are documented in the schema. The description adds no information about any parameters beyond implying that 'ticker' is needed. It doesn't explain what 'limit', 'order', 'sort', 'params', or the various 'timestamp' fields do, leaving all parameters semantically undefined and unusable without external knowledge.

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

Purpose3/5

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

The description 'Get trades for a ticker symbol' states a clear verb ('Get') and resource ('trades for a ticker symbol'), making the basic purpose understandable. However, it lacks specificity about what 'trades' means in this context (e.g., historical trades, real-time trades, or something else) and doesn't distinguish it from sibling tools like 'get_last_trade' or 'list_futures_trades', leaving ambiguity about its exact scope.

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 doesn't mention any prerequisites, exclusions, or comparisons to sibling tools (e.g., 'get_last_trade' for the most recent trade or 'list_futures_trades' for futures data), leaving the agent to infer usage from the tool name alone, which is insufficient for effective tool selection.

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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