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livetennisapi-mcp

by io.github.livetennisapi

Model analysis

get_match_analysis
Read-onlyIdempotent

Model analysis for a match: predicted win probability, the model's thesis and the key factors behind it. 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.
thesisNoNarrative view.
messageYesHuman-readable summary. Identical to the text content, so either half can be used alone.
profileNoQuantitative view.

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint and idempotentHint, so the description's main contribution is the ULTRA plan requirement. It does not add details about rate limits, data freshness, or other behavioral traits beyond what annotations provide.

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?

Two sentences: first states output, second states requirement. Concise and front-loaded. Could improve by moving requirement earlier but overall efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the presence of an output schema, the description does not need to detail return values. It adequately covers purpose and requirement but lacks usage context and behavioral details. Adequate for a simple read-only tool.

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?

With 100% schema description coverage, baseline is 3. The description adds where to obtain match_id (from get_live_matches, etc.), which provides helpful context but is not critical.

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?

Description clearly states it provides model analysis including predicted win probability, thesis, and key factors. However, it does not explicitly differentiate from sibling tools like get_match_odds or get_match_score, though the content is distinct.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool vs alternatives like get_match or get_match_odds. The ULTRA plan requirement is mentioned but doesn't help with selection among siblings.

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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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