Retrieves highly specific and unique statistical aggregates for teams across a season (e.g. successful dribbles, cross accuracy, fouls won). [CRITICAL]: Requires a valid seasonId obtained from getConfigTreeMini.
| Name | Required | Description | Default |
|---|---|---|---|
| seasonId | Yes | The unique numeric ID of the season. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must disclose behavioral traits, but it only states that the tool retrieves data and requires a seasonId. It does not explain return value structure, potential performance implications, error conditions, or other operational behavior, leaving a significant transparency gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the core purpose and examples, and the critical prerequisite is clearly flagged. Every word earns its place; there is no wasteful repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter tool, the description is reasonably complete: it covers purpose, examples, and prerequisite. However, with no output schema and no annotation fallback, it lacks details about the return format and does not address alternative tools, leaving some gaps for an agent selecting among many season-stat siblings.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already fully documents seasonId as a numeric ID, and schema coverage is 100%. The description adds valuable context by stating that the seasonId must be obtained from getConfigTreeMini, which clarifies valid parameter provenance and improves semantic understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Retrieves') and identifies the resource ('statistical aggregates for teams across a season') with concrete examples, making the primary function clear. However, it does not explicitly distinguish this tool from similar season stats siblings like get_season_team_scoring_conceding or get_season_venue_stats.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description includes a critical prerequisite ('Requires a valid seasonId obtained from getConfigTreeMini'), which is helpful usage context. But it does not state when to use this tool instead of alternatives or any exclusion criteria, so guidance remains mostly implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools have clearly distinct purposes (e.g., timelines vs stats vs lineups), but there are several closely related match-stat and season-fixture tools that could be confused, such as get_match_stats vs get_detailed_match_stats vs get_match_details_extended.
All tools use a consistent get_ prefix and snake_case, but naming conventions vary in structure (e.g., get_season_fixtures2 vs get_livescore_season_fixtures) and one tool includes an arbitrary number suffix ('fixtures2'), which is a minor deviation.
With 41 tools, the server is significantly overscoped for typical MCP use. Although the soccer domain is broad, the sheer number of highly granular tools makes it heavy and harder to navigate.
The tool set covers nearly every aspect of soccer data: fixtures, live scores, match details, standings, top scorers, injuries, referees, team streaks, and more. Minor gaps exist, such as no direct team search or player match performance, but the surface is otherwise comprehensive.