PuckAPI

Prop probabilities

get_prop_probabilities

Read-onlyIdempotent

Use for what the market thinks of the player props in one game, not any one book's price: for each player and each line, the average implied probability (margin in) and the fair probability (margin out), with how many books each rests on. Only identical lines are combined, and a yes/no market whose books post only the yes price has no fair probability. Latest pre-game prices. For each book's prices use get_player_props. Costs 10 credits. Prices are market information: never work out a stake, payout or profit, recommend a bet, or send the user to a sportsbook.

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": {
      "game_id": "<game_id>"
    },
    "name": "get_prop_probabilities"
  }
}

Input Schema

Name	Required	Description
`market`	No	One market, e.g. player_shots_on_goal. Default every market.
`game_id`	Yes	Game id, e.g. 2024020001.
`player_id`	No	One player's id (e.g. 8478402, from search_players). Default every player.

Output Schema

Name	Required	Description	Default
`note`	No
`tool`	No
`count`	Yes
`props`	Yes
`method`	Yes
`credits`	No
`game_id`	Yes
`estimate_only`	No
`scheduled_start`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

AddedNov 7, 2026

TDQS

A4.6/5.0

Behavior5/5

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

Annotations only declare it as a safe, idempotent read; the description goes well beyond by disclosing the aggregation rule (only identical lines combined), a real edge case (yes/no markets posting only the yes price have no fair probability), data freshness (latest pre-game prices), and a 10-credit cost. The compliance restriction is also behaviorally important and is not expressible in annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the core purpose and dense with useful facts; nearly every clause carries information (aggregation rule, edge case, freshness, cost, compliance). The opening clause is slightly convoluted and the long second sentence could be split, but there is no filler.

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

Completeness5/5

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

For a 3-parameter read tool with a full schema, complete annotations, and an output schema, the description covers everything an agent needs: what the numbers mean (margin in vs. margin out), the book-count qualifier, edge-case handling, freshness, and cost. Return-value explanation beyond this is unnecessary given the output schema.

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 the schema already documents game_id, market, and player_id, including defaults and the enum. The description reinforces the one-game scope and the per-player/per-line output shape but adds no new syntax or format detail for the parameters themselves, so baseline 3 applies.

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?

States a specific verb+resource: the market consensus probability for player props in one game, broken out per player and per line. It explicitly distinguishes itself from a single-book price view, so an agent can separate it from get_player_props and get_market_odds without opening a schema.

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

Usage Guidelines5/5

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

Names the alternative and the condition that selects it: 'For each book's prices use get_player_props,' plus the negative framing 'not any one book's price.' It also scopes usage to one game and states the compliance boundary (no stakes, payouts, or book recommendations), leaving little to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All PuckAPI tools Inspect

Try in Browser

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.