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mcp-server-polymarket

mcp-server-polymarket

by tukorama
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

Get an event's live volume

get_event_live_volume
Read-onlyIdempotent

Retrieves cumulative taker volume in shares for each market in a Polymarket event and the event total, helping compare market activity.

Instructions

Cumulative taker volume in shares for each market of an event, and the total.

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": {
      "event_id": "<event_id>"
    },
    "name": "get_event_live_volume"
  }
}

Input Schema

NameRequiredDescriptionDefault
event_idYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.3/5.0
Behavior3/5

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

Annotations already declare readOnly, idempotent, openWorld, and non-destructive, so the safety profile is fully covered. The description adds that values are cumulative and denominated in shares, plus the per-market plus total shape, which is genuine value. However, it says nothing about what 'live' means here — freshness, polling cadence, or whether the number resets — which is the key behavioral question for a live-metric tool.

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?

A single sentence with zero filler, front-loaded with the metric and followed by its aggregation scope. Nothing is redundant and nothing needs trimming.

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?

An output schema exists, so the return shape needn't be re-explained, and the tool is structurally simple with one parameter. Still missing are the meaning of 'live' (freshness/snapshot semantics) and any hint about the event_id source, which an agent would need to call this correctly in practice.

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 event_id carries no documentation anywhere; the description only implies it indirectly via 'for each market of an event'. It does not state the identifier format or where an event_id comes from. With a single, name-transparent parameter this is adequate but not compensatory.

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 names a specific metric (cumulative taker volume in shares), a specific scope (each market of an event), and an aggregation (the total). An agent can tell it apart from generic market tools like get_market_trading_info by the per-event breakdown. It stops short of naming any sibling explicitly, so it isn't a 5.

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?

There is no when-to-use or when-not-to-use guidance, and no alternative tool is named for related volume or activity queries. The agent must infer that this is the tool for event-level live volume purely from the name and metric description.

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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