Skip to main content
Glama

livetennisapi-mcp

by io.github.livetennisapi

Head-to-head

get_h2h
Read-onlyIdempotent

The all-time record between two players, across BOTH halves of the product: the results archive (1968–2022) plus our own completed matches (2023 onward). Names are the keys — an ambiguous fragment returns the candidate list to choose from rather than guessing. Totals count only meetings with a known winner; walkovers and retirements are part of the record and each meeting carries its outcome. Requires the BASIC plan or any History plan.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
player1YesFirst player name (fragment, min 3 chars), e.g. "federer".
player2YesSecond player name (fragment, min 3 chars), e.g. "nadal".

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.
totalsNoThe headline record.
messageYesHuman-readable summary. Identical to the text content, so either half can be used alone.
playersNoThe resolved names; null when no player matches the fragments.
meetingsNoIndividual meetings, newest first, capped at 200.
by_surfaceNoDecided wins per surface; keys are surface names plus "unknown".

TDQS

A4.7/5.0
Behavior5/5

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

Beyond the readOnly/idempotent annotations, the description discloses critical behavioral details: ambiguous fragments return a candidate list, totals exclude matches without a known winner, walkovers/retirements are included, and each meeting carries an outcome. Also states plan requirements.

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?

Four sentences, each conveying essential information with no redundancy. The main purpose is front-loaded, followed by input behavior, counting rules, and access requirements. Every sentence earns its place.

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?

The tool has only two parameters, an output schema, and strong annotations. The description covers purpose, scope, edge cases, counting semantics, and access requirements, 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.

Parameters4/5

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

The schema already fully documents both parameters with examples. The description adds value by explaining that names are keys and that ambiguous fragments trigger a candidate list, enriching the semantic understanding beyond the schema.

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's function: retrieving the all-time head-to-head record between two players across both the archive (1968–2022) and completed matches (2023 onward). This specific verb+resource+scope distinguishes it from sibling tools like get_archive_career or get_match.

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?

Provides clear context on when to use (for head-to-head records) and how input works (fragments, ambiguity handling). It doesn't explicitly name exclusions or alternatives, but no sibling tool serves the same purpose, so the guidance is strong.

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