Skip to main content
Glama

livetennisapi-mcp

by io.github.livetennisapi

Match statistics

get_match_statistics
Read-onlyIdempotent

In-play (or final) statistics for one match, in TWO families kept deliberately separate: DERIVED is rebuilt from the point-by-point record (holds/breaks, break points, service/return points); MEASURED is counted upstream and includes what no point record can yield — aces, double faults, the serve split, winners/unforced errors. Measured coverage varies by tour; absent fields are omitted, never zero-filled. Requires the ULTRA plan.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
match_idYesMatch id, as returned by get_live_matches, get_upcoming_matches or get_recent_results.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
okYesTrue 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.
messageYesHuman-readable summary. Identical to the text content, so either half can be used alone.
statisticsNoThe statistics.

TDQS

A4.5/5.0
Behavior5/5

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

Beyond the annotations (read-only, open-world), the description discloses that measured statistics coverage varies by tour, absent fields are omitted rather than zero-filled, and the two families are deliberately kept separate. These are nuanced behavioral details not available from annotations alone.

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 compact and front-loaded with the core purpose. Each sentence contributes meaningful detail—families, coverage variance, omission behavior, and access requirement—with no redundant 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?

An output schema exists, so the description need not enumerate return fields. It covers the important contextual aspects: match scope, in-play/final status, data families, coverage variability, omission policy, and plan requirement, making it complete for the tool's complexity.

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 already fully documents the single match_id parameter with a description. The tool description adds no extra parameter semantics beyond confirming it applies to 'one match,' so it meets the baseline for full schema coverage.

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 provides statistics for one match and distinguishes the two data families (DERIVED vs MEASURED), making the resource and intent unambiguous relative to sibling tools like get_match_score or get_match_analysis.

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?

The description implies use for retrieving match statistics and notes the ULTRA plan requirement, giving clear context. However, it doesn't explicitly state when not to use alternative tools, so it stops short of full alternatives guidance.

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

All livetennisapi-mcp toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.9/5.0
Disambiguation4/5

The tool set is largely distinct with clear resource/action pairs. Potential confusion exists between get_match and get_match_score (both return match information), and get_fixtures vs get_upcoming_matches (both list upcoming matches), but descriptions clarify the specific use cases for each.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern using either 'get_' or 'search_'. This makes the API highly predictable and easy to navigate, with no stylistic deviations.

Tool Count3/5

With 24 tools, the server is on the heavy end of the typical range. The broad scope (live, archive, charting, rankings, tournaments) justifies the count, but it borders on overwhelming and requires careful categorization.

Completeness4/5

The server covers the core lifecycle of a tennis information API: searching players/tournaments, retrieving profiles/rankings, live scores and detailed match analysis, historical results, and head-to-head records. Minor gaps like tournament draws or standings are missing, but the primary use cases are well covered.

Resources