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UFCalendar Fight API — MMA MCP server

Get a stat leaderboard

get_leaderboard
Read-onlyIdempotent

One statistical leaderboard for one promotion from UFCalendar's Record Book rollup — career, single-fight, single-round, division or event boards across 48 metrics (wins, finishes, significant strikes, takedowns, control time, finish rate and more), optionally narrowed to a division, a country or active fighters. Ranked, with the sample size behind each value.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
orgYesPromotion slug (required — boards are per promotion).
limitNoRows, default 25.
metricYesBoard metric, e.g. "wins", "finishes", "sig_strikes_landed", "fastest_knockout", "most_finishes_event", "finish_rate".
countryNoISO-3166 alpha-2 nationality, e.g. "BR" — fighters from that country. Not with population=active.
divisionNoOne weight class, e.g. "lightweight", "womens-strawweight".
populationNoall (default) = everyone who fought in the promotion; active = a bout in the last ~18 months.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already establish readOnlyHint, idempotentHint, and destructiveHint, so safety is covered. The description adds behavioral context beyond that: it is per-promotion, ranked, and includes the sample size behind each value, which helps the agent understand what the response represents.

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 a single tightly packed sentence that front-loads the core purpose and then adds filters and output behavior efficiently. Every phrase adds information, and the 'and more' avoids an unwieldy metric list.

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

Completeness4/5

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

The description, combined with a fully documented schema, gives the agent enough to call the tool correctly: what it returns, how it is scoped, and what filters narrow it. There is no output schema, but mentioning ranking and sample size covers the most important response characteristics.

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?

Schema description coverage is 100%, so the schema already documents all parameters. The description adds some grouping context—'optionally narrowed to a division, a country or active fighters'—but does not materially extend the meaning of org, metric, limit, or enums beyond what the schema provides.

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 names a specific verb and resource: getting 'one statistical leaderboard for one promotion' from UFCalendar's Record Book rollup. It enumerates board types and metric examples, so the tool is clearly distinguishable from siblings like get_record_book or get_rankings without opening the schema.

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?

It provides clear context: use this when you need a ranked, single-metric leaderboard for a promotion, optionally filtered by division, country, or active fighters. It does not explicitly name alternatives or when-not-to-use conditions, but the context is strong enough for an agent to route correctly.

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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