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sportsdata-mcp

sportsdata-mcp

by DanielTomaro13
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

kalshi_trades

Read-onlyIdempotent

Fetch recent public sports trades, optionally filtered by market ticker. Uses cursor pagination to navigate results.

Instructions

Recent public trades, optionally for one market ticker. Paginated by cursor.

Returns: {cursor, trades:[{trade_id, ticker, count, yes_price, no_price, taker_side, created_time}]}

Auth: none needed.

Also answers this: polymarket_trades, polymarket_holders.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "kalshi_trades"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNoPage size (1-1000).
cursorNoPagination cursor.
max_tsNoUnix-seconds upper bound.
min_tsNoUnix-seconds lower bound.
tickerNoFilter to one market.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed5 schema fields changedv0.24.0
    • addedInput schema / properties / cursor / description
      Added value: +"Pagination cursor."
    • addedInput schema / properties / limit / description
      Added value: +"Page size (1-1000)."
    • addedInput schema / properties / max_ts / description
      Added value: +"Unix-seconds upper bound."
    • addedInput schema / properties / min_ts / description
      Added value: +"Unix-seconds lower bound."
    • addedInput schema / properties / ticker / description
      Added value: +"Filter to one market."
  2. Addedv0.1.1

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint. The description adds 'Auth: none needed', pagination via cursor, and the exact return structure, all of which are behavioral details beyond the annotation. There is no contradiction with 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 three concise sentences plus an inline return format and auth note, all front-loaded with the purpose. There is no filler or redundancy; every sentence carries value.

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

Completeness4/5

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

The description provides the return format explicitly, which compensates for the absence of an output schema. It covers auth and pagination, and hints at alternatives. It does not explain field semantics or ordering, but these are minor given the schema and self-explanatory field names.

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 100%, so each parameter is already documented. The description adds minimal new parameter meaning—it reiterates pagination via cursor and optional ticker filtering, but does not enrich beyond the schema. At high coverage, baseline of 3 is appropriate.

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 'Recent public trades, optionally for one market ticker' and mentions pagination by cursor. This gives a specific verb, resource, and scope. It also distinguishes itself from sibling tools by explicitly noting it also answers polymarket_trades and polymarket_holders, avoiding confusion with those.

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 provides a clear context for when to use the tool (for recent public trades, optionally filtered by ticker) and explicitly states that it also answers the queries of polymarket_trades and polymarket_holders, serving as a routing hint to prefer this tool for those purposes. It does not list exclusions for other alternatives, but the provided guidance is sufficient.

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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