About Batru
Batru is a read-only MCP server for game draft and matchup analysis in Dota 2, Deadlock, and Marvel Rivals. It queries batru.gg's live API for calibrated model predictions rather than running models locally.
Key features
- 01Predict calibrated team win rates
- 02Recommend the next Dota 2 pick
- 03Retrieve hero counter matchups
- 04Normalize hero names and aliases
- 05Analyze Deadlock drafts
Use cases
- 01Compare win chances during a Dota 2 draft
- 02Choose a Dota 2 hero for the next pick
- 03Review a hero's matchup counters
- 04Estimate outcomes for a Deadlock draft
MCP support
The hosted Streamable HTTP endpoint exposes read-only game-analysis tools to MCP clients. A legacy PyPI package can also run a reduced stdio server that proxies the same live API.
Configuration
Remote servers need no local install. Pick your client, then copy the config or install in one click.
https://batru.gg/mcpclaude mcp add --transport http batru https://batru.gg/mcp{"mcpServers":{"batru":{"type":"http","url":"https://batru.gg/mcp"}}}Open in Cursor{"servers":{"batru":{"type":"http","url":"https://batru.gg/mcp"}}}Open in VS Code{"mcpServers":{"batru":{"type":"http","url":"https://batru.gg/mcp"}}}{"mcpServers":{"batru":{"serverUrl":"https://batru.gg/mcp"}}}Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.
Tools
17| Parameter | Type | Required | Description |
|---|---|---|---|
| game | string | No | "dota2" (default), "deadlock", or "marvel-rivals". |
| query | string | Yes | A hero name, alias or short name as the user typed it. Pass an EMPTY string to list the game's full roster instead. |
| context | string | Yes | Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution." |
Details
From the project READMEbatru-mcp
Important
Use the hosted endpoint — no install needed. Add
https://batru.gg/mcpto Claude, ChatGPT, Cursor or any MCP client and you get the newest tool set (31 read-only tools across Dota 2, Deadlock and Marvel Rivals, always in sync with the live site). Setup guide: https://batru.gg/developersThe local PyPI package described below (
uvx batru-mcp) is legacy and no longer updated — it is frozen at an early version with a reduced tool set. It still works (it proxies the same live API), but the hosted endpoint is the canonical distribution.
A minimal, read-only MCP server over batru.gg's live API, so your LLM can answer Dota 2 / Deadlock draft, counter and win-rate questions with real, calibrated model predictions instead of guessing from memory.
It is a thin wrapper around batru.gg's public endpoints — no model runs locally; every number comes from the same production model the website serves.
Why calibrated matters
batru.gg's model is trained on ~20M real matches and calibrated: a reported 60% win rate corresponds to an empirically observed ~60% win rate. We deliberately do not headline a raw "accuracy" number — accuracy alone is misleading for win prediction. What you get from these tools are probabilities you can trust at face value. The tool descriptions instruct the host LLM to report these numbers verbatim and never invent matchup data.
Tools
| Tool | What it does |
|---|---|
lookup_hero(query, game="dota2") | Normalise a name/alias/shortName to {id, displayName, shortName}. game ∈ {dota2, deadlock}. |
predict_dota_winrate(my_heroes, enemy_heroes, my_side="radiant") | Calibrated win-rate % for both teams (partial drafts OK; empty → 50/50). |
recommend_dota_pick(my_heroes, enemy_heroes, my_side="radiant") | Top-3 heroes to pick next, each with its calibrated win rate. |
get_dota_counters(hero, limit=12) | Real matchup table: who this hero beats / loses to, with win rate % and sample size. |
predict_deadlock_draft(team0_heroes, team1_heroes) | Calibrated win-rate % for a Deadlock 6v6 (6 heroes per team). |
Hero names are accepted in any form (e.g. am, anti mage, Anti-Mage) and normalised internally — the backend silently drops names it doesn't recognise, so normalising first keeps predictions honest.
Install
Requires uv (or any way to run a Python 3.12+ package from PyPI):
uvx batru-mcp # fetches from PyPI and starts the stdio MCP server
Configuration is via the BATRU_API_BASE environment variable (default https://batru.gg) — you normally don't need to set anything.
Claude Desktop config
Add to claude_desktop_config.json (macOS: ~/Library/Application Support/Claude/claude_desktop_config.json):
{
"mcpServers": {
"batru": {
"command": "uvx",
"args": ["batru-mcp"]
}
}
}
Restart Claude Desktop; the batru tools appear in the tool picker. Claude Code:
claude mcp add batru -- uvx batru-mcp.
Development
git clone https://github.com/batrugg/batru-mcp && cd batru-mcp
uv sync
uv run batru-mcp # run the server from the checkout (blocks, waiting on stdin)
For a Claude Desktop pointing at the checkout, use
"command": "uv", "args": ["run", "--directory", "/absolute/path/to/batru-mcp", "batru-mcp"].
Tests
uv run pytest # offline: hero normalisation + draft assembly
uv run pytest -m live # also hits the real batru.gg API
Prefer programmatic access from Python instead of MCP? pip install batru — the
official batru SDK.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.