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fanduel_sportsbook_live

Retrieve in-play sportsbook events with live markets and odds for a chosen sport and U.S. state; use sport live counts to switch event types.

Instructions

FanDuel Sportsbook live betting events. Returns events that are in play now for one sport, with their live markets and odds. tabs lists every sport with its live-event count (live_count); pass event_type_id to load another sport. Without it the Sportsbook's default sport is returned and reported in event_type_id.

Input Schema

NameRequiredDescriptionDefault
stateNoU.S. market to query (prices and offered markets differ by state); default nj
market_typeNoKeep only these market types (repeat the parameter or comma-separate), for example `MONEY_LINE`. Valid values are listed in the response `market_types`; unmatched types return no markets
event_type_idNoSport id: 6423 American Football; 1 Soccer; 7522 Basketball; 3 Golf; 7511 Baseball; 7524 Ice Hockey; 2 Tennis; 26420387 Mixed Martial Arts; 2593174 Table Tennis; 3503 Darts; 6 Boxing; 5 Rugby Union; 4 Cricket; 8 Motor Sport; 1477 Rugby League; 6422 Snooker; 468328 Handball; 28608997 Lacrosse; 998917 Volleyball, 4726642 Surfing, 10 Special Bets and 2378961 Politics; availability differs by market (Volleyball is also offered in NJ, PA, CO and AZ), and a sport a market does not offer returns 404
exclude_marketsNoReturn events without their markets (a cheap event listing); `market_types` is still returned

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.17.16

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and mostly succeeds: it discloses that results are limited to currently-in-play events for a single sport, that the default sport is silently substituted when no id is given, and that the response echoes the resolved `event_type_id` and includes `tabs`. It omits any caveats on freshness, rate limits, or empty-result behavior when a sport has no live games.

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?

Three sentences, front-loaded with the purpose, then the discovery workflow, then the default behavior. Dense but every sentence carries actionable information; minor cost is that the third sentence packs two ideas (default sport and response echo) together.

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?

No output schema and no annotations, so the description must supply the behavioral picture, and it covers scope, default-sport resolution, sport discovery, and market filtering reasonably well. Remaining gaps (what an event object contains, behavior when zero live events exist) are modest for a read-only listing tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3, but the description adds real value the schema does not: the default-sport fallback semantics of `event_type_id`, the presence of the `tabs`/`live_count` structure used to discover valid ids, and the fact that a resolved sport id is reported back in the response.

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+scope: returns live (in-play) events for one sport with live markets and odds. This clearly separates it from siblings like fanduel_sportsbook_live_count (counts), live_scores (scores) and live_data (general data), which an agent can distinguish without opening schemas.

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?

Explains how to iterate sports: use `tabs` for per-sport `live_count`, then pass `event_type_id` to switch sports, with a documented fallback to the default sport. It gives clear operational context but never names an alternative tool or says when not to use this one (e.g. vs live_data or live_scores).

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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