MCP Dota 2 Match Analysis Server

get_pro_matches

Fetch recent professional Dota 2 matches as a flat list, filtering by team, league, tier, or recent days. Supports head-to-head and team-specific queries.

Instructions

Get recent professional Dota 2 matches as a flat list.

Returns individual matches without series grouping. Use get_tournament_series for bracket/series analysis.

Args: limit: Maximum matches to return (default 50) tier: Filter by league tier (premium, professional, amateur) team1_name: Filter by first team (fuzzy match). Alone: all matches for team. team2_name: Filter by second team (fuzzy match). With team1: head-to-head matches. league_name: Filter by league/tournament name (contains, case-insensitive) days_back: Only return matches from last N days

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_pro_matches"
  }
}

Input Schema

Name	Required	Description	Default
`tier`	No
`limit`	No
`days_back`	No
`team1_name`	No
`team2_name`	No
`league_name`	No

Output Schema

Name	Required	Description	Default
`error`	No
`matches`	No
`success`	Yes
`total_matches`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.2.0Jul 31, 2026

TDQS

A4.7/5.0

Behavior4/5

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

With no annotations, the description carries full burden. It discloses several behavioral details: returns a flat list without series grouping, fuzzy matching on team names, case-insensitive league name matching, and head-to-head behavior when both team parameters are combined. It does not discuss return format (covered by output schema) or side effects, so it's not perfect.

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 short and front-loaded with the primary purpose, then a single-line alternative hint, then a clean Args list. No filler.

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?

For a tool with six optional parameters and an output schema, the description covers the key use cases and parameter interactions. It could clarify the default time window for 'recent' matches, but overall it's quite complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, but the description compensates thoroughly by explaining all six parameters with defaults (limit 50), filter semantics (tier levels), and special behavior (team1 alone vs with team2; league_name contains case-insensitive).

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 opens with a clear verb+resource: 'Get recent professional Dota 2 matches as a flat list.' It further distinguishes from a sibling by stating 'Returns individual matches without series grouping. Use get_tournament_series for bracket/series analysis.'

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?

Explicitly names get_tournament_series as the alternative for bracket/series analysis, and clarifies that this tool returns flat individual matches. This gives clear when-to-use guidance.

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