MCP server

Batru — Competitive Game Intelligence for AI Agents Official

gg.batru/batru-mcp

Checked 26 Oct 2026, 08:29 UTC · Connected to it and listed its tools

Live competitive-game predictions, meta data and decision tools for AI agents.

Working at last checkVerified publisher: batru.ggAbout 10,173 tokens per request once connected17 tools

Website Source

https://batru.gg/mcp

At a glance

Type: MCP server
Publisher: batru.gg (verified by the MCP Registry)
Status: Working at last check
Tools: 17
Token cost: About 10,173 tokens per request
Sets up in: Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, VS Code, Antigravity, ChatGPT, OpenAI API, Grok
Last checked: 26 Oct 2026, 08:29 UTC

Connect it to your agent

Add to Cursor Add to VS Code VS Code Insiders

Opens the app, which shows the server and asks you to confirm. For other apps, copy the setup below.

Claude Code

claude mcp add --transport http batru-mcp https://batru.gg/mcp

Claude Desktop

Settings → Connectors → Add custom connector, and paste the URL.

Codex (config.toml)

[mcp_servers.batru-mcp]
url = "https://batru.gg/mcp"

Gemini CLI

{"mcpServers":{"batru-mcp":{"httpUrl":"https://batru.gg/mcp"}}}

Cursor

{"mcpServers":{"batru-mcp":{"url":"https://batru.gg/mcp"}}}

VS Code

{"servers":{"batru-mcp":{"type":"http","url":"https://batru.gg/mcp"}}}

Antigravity

agy mcp add batru-mcp https://batru.gg/mcp

ChatGPT

Settings → Apps & Connectors → Advanced settings: turn on Developer mode, then Create a connector and paste the URL. Which plans can do this varies.

OpenAI API (Responses tools)

{"type":"mcp","server_label":"batru-mcp","server_url":"https://batru.gg/mcp","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"batru-mcp","server_url":"https://batru.gg/mcp"}

Tools

analyze_draft ~954 tokens
Analyze a draft and render an interactive Batru win-rate board. Use this for visual draft, matchup, win-probability, or next-pick questions in Dota 2, Deadlock, or Marvel Rivals. It combines the existing prediction and recommendation tools into one stable structured result. Clients that
fetch ~409 tokens
Fetch the full live document behind a `search` result id. Ids look like `dota2:counters:axe`, `deadlock:tier-list`, `marvel-rivals:synergy:mantis`, `deadlock:ban-rates`, `dota2:tournament:ti-2026` or `model:track-record`. Returns {id, title, text, url} where `text` is the document'
get_ban_rates ~440 tokens
Most-banned heroes — measured draft-phase ban rates for Deadlock or Marvel Rivals. Args: game: "deadlock" or "marvel-rivals" (ranked Dota has no ban-phase export — for pro Dota bans use get_tournament_stats). limit: Max heroes to return (default 15). Report numb
get_counters ~612 tokens
Who counters a hero (and who it beats) — measured matchup win rates for Dota 2, Deadlock or Marvel Rivals. Opponents this hero performs BEST and WORST against, by real observed win rate with sample sizes — empirical meta data, not a guess. The hero name is normalised internally. Ar
get_hero_momentum ~546 tokens
Which heroes are rising or falling right now — week-over-week win-rate movement. Momentum from batru.gg's rolling match aggregation for Dota 2, Deadlock or Marvel Rivals: the biggest movers of the current window, or one hero's trend when `hero` is given. Args: game: "dota2"
get_matchup ~514 tokens
One hero vs one opponent — the measured head-to-head win rate in Dota 2, Deadlock or Marvel Rivals. The direct matchup number ("does X beat Y?") from real games, with the sample size. Names are normalised internally. Args: game: "dota2", "deadlock", or "marvel-rivals".
get_model_track_record ~604 tokens
Get batru.gg's public model evaluation ledger — every weekly test, wins AND losses. batru.gg publishes EVERY champion-vs-challenger evaluation of its Dota 2 model (promoted or rejected), auto-generated from the promotion gate's append-only log — nothing is hand-picked. Use this when a u
get_more_tools ~107 tokens
Check for additional tools whenever your task might benefit from specialized capabilities - even if existing tools could work as a fallback.
get_synergy ~602 tokens
Best teammates / duo partners for a hero — measured together-win-rates for Dota 2, Deadlock or Marvel Rivals. Allies this hero wins MOST and LEAST with, by real observed win rate when picked together (with sample sizes). Covers Marvel Rivals team-ups too. The hero name is normalised int
get_tier_list ~664 tokens
Best heroes right now — the current-patch tier list for Dota 2, Deadlock or Marvel Rivals. Empirical rankings from batru.gg's match aggregation over real games (not a guess); heroes come sorted best-first. Optionally filter to a skill bracket with `rank`. Args: game: "dota2
get_tournament_game_stats ~658 tokens
Per-game BOX SCORES from parsed replays of a pro Dota 2 tournament. For each game: lane winners at 10 minutes, every player's hero, lane, K/D/A, GPM, net worth and key item timings, first blood, Roshans, and comeback flags. Filter by team, stage, or a single match_id. Args:
get_tournament_stats ~565 tokens
TI / EWC pro tournament stats — actual most-picked, most-banned and win rates per hero. Real recorded results from the official drafts of every game at a covered pro Dota 2 event (The International, Esports World Cup, ...) — small-sample records, not calibrated probabilities. Answers "m
lookup_hero ~573 tokens
Normalise a hero name/alias/shortName to its canonical identity — or list the whole roster. Use this to turn messy user input ("am", "anti mage", "Anti-Mage") into the exact key batru.gg expects before calling the prediction tools. The backend SILENTLY DROPS hero names it doesn't recogn
predict_winrate ~900 tokens
Which team wins this draft — CALIBRATED win probability for Dota 2, Deadlock or Marvel Rivals. Backed by batru.gg's per-game production models (built on 140M+ real matches and calibrated: a reported 60% reflects a real ~60% empirical win rate — not a guess). Hero names are normalised in
predict_winrate_batch ~759 tokens
Score MANY candidate next-picks for a Dota 2 draft in ONE call — calibrated win rate + delta each. Use this instead of looping predict_winrate over candidates: the whole batch runs as a single model invoke server-side. For each candidate you get the CALIBRATED team win rate after adding
recommend_pick ~776 tokens
Best heroes to pick next against this draft — Dota 2, Deadlock or Marvel Rivals. Per-game semantics: - dota2: top 3 picks scored by the CALIBRATED draft model (each with the calibrated team win rate after adding that hero); `my_side` applies. - deadlock / marvel-rivals: ranked by
search ~490 tokens
Search batru.gg's live competitive datasets for Dota 2, Deadlock and Marvel Rivals. Finds the right document for a question about hero counters, hero synergies /duos, current-patch tier lists, ban rates, pro tournament results (TI, Esports World Cup) or the prediction model's public eva

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