livetennisapi-mcp

Match market prices

get_match_odds

Read-onlyIdempotent

Retrieve match-winner market prices for a match, including implied probability per player and bid, ask, and mid quotes. Use after checking has_market to confirm odds exist for the match.

Instructions

Match-winner market prices for a match — implied probability per player, with bid, ask and mid. Requires the PRO plan. Match rows carry has_market — check it first; a match with no market mapped has no prices to return.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`limit`	No	Maximum price points to return (1-200).
`match_id`	Yes	Match id, as returned by get_live_matches, get_upcoming_matches or get_recent_results.

Output Schema

TableJSON Schema

Name	Required	Description
`ok`	Yes	True when the call returned data. False for a tier wall, a missing or rejected key, or an empty result — all of which are normal states with a clear remedy, not failures.
`market`	No	The match-winner market.
`message`	Yes	Human-readable summary. Identical to the text content, so either half can be used alone.

Schema Changelog

Changes observed during successful MCP inspections.

Addedv1.3.0Aug 5, 2026
Removedv1.2.0Jul 22, 2026
First observedv1.0.4Jul 22, 2026

TDQS

A4.3/5.0

Behavior4/5

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

Annotations already declare readOnly, idempotent, and non-destructive behavior, so the description correctly adds context beyond them: the PRO plan requirement and the empty-result behavior when no market is mapped. This gives the agent practical expectations without contradicting the 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?

Two dense sentences with no filler. The core purpose is front-loaded, followed by the most important usage caveats, making every sentence valuable.

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 read-only lookup with a rich output schema, the description covers prerequisites (PRO plan), preconditions (has_market), and empty-result behavior. Nothing essential is missing for an agent to call and interpret the tool correctly.

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?

Input schema covers both parameters fully (match_id and limit with bounds/default), so the description does not need to add parameter details. It contributes only indirectly by explaining the match-level has_market precondition, which is not a parameter semantic.

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 states exactly what the tool returns: match-winner market prices with implied probability per player and bid/ask/mid. This precise scope clearly distinguishes it from sibling tools like get_match_score or get_match_analysis, which cover different data.

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?

It gives clear context for when to call the tool by requiring the PRO plan and instructing the agent to check has_market first. It does not explicitly name alternatives or exclusions, but the precondition guidance is enough to route correct usage.

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