Retrieves detailed stadium and venue statistics for a season (attendance, capacities). [CRITICAL]: Requires a valid seasonId obtained from getConfigTreeMini.
| Name | Required | Description | Default |
|---|---|---|---|
| venueId | Yes | The unique numeric ID. | |
| seasonId | Yes | The unique numeric ID. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses a key behavioral dependency (seasonId from getConfigTreeMini) and 'Retrieves' implies read-only. However, it doesn't specify return format, pagination, or other behavioral traits, leaving some uncertainty.
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 every word earns its place. The [CRITICAL] annotation effectively highlights the dependency without extra fluff.
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 simple two-parameter read tool with no annotations and no output schema, the description provides purpose, example data types, and the critical dependency. It doesn't describe return shape or error behavior, but the information given is sufficient for correct invocation in most cases.
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?
Schema coverage is 100% but both parameter descriptions are generic ('The unique numeric ID'). The description adds meaningful context: it reveals that seasonId must be obtained from getConfigTreeMini, and the tool name/title implies venueId refers to a stadium/venue, going beyond the schema's generic descriptions.
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 clearly states the tool retrieves 'detailed stadium and venue statistics for a season' with examples (attendance, capacities). This specific verb+resource combination distinguishes it from sibling tools, none of which target 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 explicitly states the critical prerequisite: a valid seasonId must come from getConfigTreeMini. This provides clear context for when the tool can be invoked. It doesn't mention alternatives or exclusions, but the dependency is the key usage guidance.
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.