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sportsdata-mcp

sportsdata-mcp

by DanielTomaro13
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

kalshi_orderbook

Read-onlyIdempotent

Retrieve the order book for a Kalshi market, showing resting yes and no bids by price level to evaluate market depth.

Instructions

Order book for one market — resting yes/no bids by price level (dollar-denominated).

Returns: {orderbook_fp:{yes_dollars:[[price, size], …], no_dollars:[[price, size], …]}} (empty arrays when nothing is resting)

Auth: none needed.

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": {
      "ticker": "<ticker>"
    },
    "name": "kalshi_orderbook"
  }
}

Input Schema

NameRequiredDescriptionDefault
depthNoMax price levels per side.
tickerYesMarket ticker. Required — part of the URL path.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv0.24.0
    • addedInput schema / properties / depth / description
      Added value: +"Max price levels per side."
    • addedInput schema / properties / ticker / description
      Added value: +"Market ticker. Required — part of the URL path."
  2. Addedv0.1.1

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint, covering safety and idempotency. The description adds useful behavioral details: the exact return shape (orderbook_fp with yes_dollars and no_dollars arrays), empty arrays when nothing is resting, and no authentication requirement. This goes beyond annotations, though it does not discuss ordering, pagination, or failure scenarios.

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 concise and well-structured: purpose in the first sentence, return format in the second, and an auth note in the third. Every sentence adds value without redundancy. It is front-loaded and easy to scan.

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?

Given the tool's simplicity, the description is nearly complete. It covers the core purpose, return structure, empty-order behavior, and authentication. Since there is no output schema, including the return shape is valuable. The only missing piece is explicit usage guidance relative to sibling tools, but that is a minor gap.

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?

The input schema provides full descriptions for both parameters (`ticker` required and `depth` with a description), so schema description coverage is 100%. The description does not add additional parameter semantics beyond what the schema already states, resulting in a baseline score of 3.

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's function: 'Order book for one market — resting yes/no bids by price level (dollar-denominated).' This specifies the action (retrieve order book), the resource (one market), and the data type (resting bids). It distinguishes from sibling tools like kalshi_candlesticks or kalshi_market by focusing on order book depth and the 'one market' scope.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for retrieving order book data for a specific market, but it does not explicitly state when to use this tool versus alternatives such as kalshi_trades or kalshi_market. No comparative or exclusionary guidance is provided, so the usage context is only implied by the tool's purpose.

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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