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DanielTomaro13

sportsdata-mcp

theoddsapi_odds

Read-onlyIdempotent

Get odds for a competition across many bookmakers, filtered by sport, market, and region.

Instructions

Odds for a competition across many bookmakers. QUOTA COSTS markets × regions per call — keep both narrow.

Returns: [{id, sport_key, sport_title, commence_time, home_team, away_team, bookmakers:[{key, title, last_update, markets:[{key:'h2h', last_update, outcomes:[{name, price, point}]}]}]}] — outcome name is a TEAM NAME, not home/away; point appears on spreads/totals only

NOTE: this shape is from the vendor's documentation and has NOT been verified against a live response (we hold no key for this provider). Treat it as approximate — inspect the actual payload before relying on a field name.

Example: EPL head-to-head across AU books {"sport": "soccer_epl", "regions": ["au"], "markets": ["h2h"]}

Auth: needs your own key in THE_ODDS_API_KEY.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sportYessport_key from theoddsapi_sports, e.g. soccer_epl, americanfootball_nfl. Required — part of the URL path.
marketsNoh2h, spreads, totals, outrights. EACH market multiplies the quota cost.
regionsNoBookmaker regions: us, us2, uk, eu, au. EACH region multiplies the quota cost.
eventIdsNoRestrict to specific event ids.
bookmakersNoSpecific bookmaker keys instead of whole regions (does not reduce quota cost).
dateFormatNoTimestamp format. One of: iso, unix.iso
oddsFormatNoPrice format. One of: decimal, american.decimal
Behavior5/5

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

The description goes well beyond the annotations by disclosing the exact return shape, clarifying that outcome `name` is a team name and `point` appears only on spreads/totals, and warning that the shape is from vendor documentation and has NOT been verified against a live response. It also notes quota cost behavior and the need for THE_ODDS_API_KEY, providing rich behavioral context.

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?

The description is fairly long but each section earns its place: purpose, quota warning, return shape, disclaimer, example, and auth note. The structure is clear with a returns block and note, though it could be slightly more concise by trimming redundant quota cost mentions already in the schema.

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?

Despite lacking an output schema, the description fully details the return structure, clarifies tricky fields, provides a runnable example, warns about data reliability, and states authentication requirements. This is complete for a read-only, idempotent odds endpoint and leaves little ambiguity for the agent.

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 schema already provides 100% coverage with descriptions for all 7 parameters, including quota cost notes for `markets` and `regions`. The description repeats the quota cost warning and gives an example, but it does not add semantic meaning beyond what the schema already offers, so the baseline score of 3 is appropriate.

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 clearly states the tool returns 'Odds for a competition across many bookmakers' and provides an example (EPL head-to-head across AU books), which makes its function evident. It does not explicitly differentiate itself from sibling tools like theoddsapi_event_odds, but the resource and scope (many bookmakers) are specific enough to distinguish it from events, scores, and historical odds.

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 gives useful guidance on parameter usage (QUOTA COSTS markets × regions per call — keep both narrow) and an example invocation. However, it does not explicitly state when to use this tool over alternatives such as theoddsapi_event_odds or theoddsapi_scores, so the selection context is implied rather than explicit.

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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