Cito API

match_summary

Read-only

COMPOSITE match card: scoreline, key context, player performances, and VOD/demo links when available.

When to use:

Match recap / default match UI
After user selects a live or completed matchId

Prefer over match_details for chat answers and default UIs. Prefer match_details for timelines, full map trees, live state, advanced packages.

Do not use when: no matchId yet (resolve from live/schedule); pure pre-match → match_preview.

Parallel-safe: yes. Upstream cost: 2–5. Example: { "game": "cs2", "matchId": "cs2-match-123", "view": "summary", "includePlayerStats": true }

Input Schema

TableJSON Schema

Name	Required	Description	Default
`game`	Yes	Game title: lol \| cs2 \| dota2 \| cod \| ufc \| tennis. Example: "cs2".
`view`	No	Payload weight. Default summary.	summary
`matchId`	Yes	Game-native match id (UFC: boutId). Example: "cs2-match-123".
`includeMedia`	No	Include demos/VODs when the API provides them.
`includePlayerStats`	No	Include player performances when available.

Output Schema

TableJSON Schema

Name	Required	Description
`ok`	Yes	true if the tool succeeded
`data`	No	Result payload when ok is true; null on error
`meta`	Yes
`error`	No
`partial`	No
`pagination`	No

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

First observedSep 1, 2026

TDQS

A4.5/5.0

Behavior4/5

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

Annotations already mark the tool as read-only and non-destructive, and the description adds non-obvious behavior: 'Parallel-safe: yes', 'Upstream cost: 2–5', and data availability caveats like 'when available'. This goes beyond the annotations, though it does not detail error cases or rate limiting.

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 well-structured with a one-line summary, bulleted usage guidance, routing notes, negative cases, and a compact example. Every section earns its place, and the most important information is front-loaded.

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?

Given the rich input schema, existing output schema, read-only annotations, and clear sibling differentiation, the description covers what an agent needs to call the tool correctly. It also includes parallel-safety and upstream cost context, making it complete for this level of complexity.

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 coverage is 100%, so the schema fully documents all five parameters. The description adds a concrete usage example and links concepts like 'player performances' and 'VOD/demo links' to the relevant parameters, but it does not add substantial meaning beyond the schema's own parameter descriptions.

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 uses a specific opening phrase, 'COMPOSITE match card', and enumerates the delivered content: scoreline, key context, player performances, and VOD/demo links. It explicitly distinguishes this tool from match_details and match_preview, so an agent can easily tell what this tool is for.

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

Usage Guidelines5/5

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

The description provides a dedicated 'When to use' section, explicit routing guidance ('Prefer over match_details'), and clear negative cases such as 'no matchId yet' and 'pure pre-match → match_preview'. This leaves no ambiguity about when to call this tool versus its siblings.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Cito API tools Inspect

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

A4.5/5.0

Disambiguation5/5

Each tool has a clearly distinct job, and the descriptions explicitly separate temporal states (live vs upcoming vs preview vs recap vs deep-dive) and interaction modes (one-best resolve vs browse search, curated tool vs raw escape hatch). Even the match/event families are carefully tiered so an agent should rarely misselect.

Naming Consistency3/5

Names are readable and grouped into recognizable families like list_*, match_*, and *_profile, but the overall convention is mixed: verb-prefixed names like resolve_entity and call_api sit alongside noun-phrase names like event_card, match_summary, and standings. Consistent snake_case prevents chaos, but there is no uniform verb_noun pattern.

Tool Count4/5

16 tools is at the upper edge of the ideal range, but the server spans multiple games and several composite read workflows, so each tool has a distinct purpose. It feels slightly heavy but not bloated.

Completeness4/5

The set covers health, discovery, entity resolution, profiles, standings, schedules, live matches, previews, recaps, and deep-dive match data, with call_api as an escape hatch for long-tail routes. Notable omissions like a standalone historical results search and some per-game upstream gaps keep it from a perfect score.

Resources

Need Help?