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Brotato Coach

by brendanlefebvreversion 0.14.1i★ –iRuns on your computer
Registry nameio.github.brendanlefebvre/spudcoach

Install

Overview

Description from the maker (original English)

Deterministic Brotato theorycrafter MCP server: facts and math, not guesses.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Other

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • You fill in yourself: SPUDCOACH_DATA

You need

  • PyPIPython’s uv installed (for the uvx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "spudcoach": {
      "command": "uvx",
      "args": [
        "spudcoach"
      ],
      "env": {
        "SPUDCOACH_DATA": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add spudcoach --env SPUDCOACH_DATA=your-value -- uvx spudcoach

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "spudcoach": {
      "command": "uvx",
      "args": [
        "spudcoach"
      ],
      "env": {
        "SPUDCOACH_DATA": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "spudcoach": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "spudcoach"
      ],
      "env": {
        "SPUDCOACH_DATA": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

  • SPUDCOACH_DATA env
    Path to a locally built brotato.json dataset (see README for how to build one — the game data itself is never distributed). Equivalent to the --data CLI flag.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 8, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account brendanlefebvre, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Otheri

  • More stars than 0% of the other 18431 servers in this category
  • Published to the registry more recently than 18% of the other 18431 servers in this category
  • Basic checks equal to or better than 100% of the other 18431 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Brotato Coach safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.14.1) reached the registry 3 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, Tethered Trust

Alternatives

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Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

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MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

Runs on your computer★ 440MITUpdated 14 months ago
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Remote Desktop Commander

by desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

Runs in the cloud★ 211Updated 3 days ago
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Tethered Trust

by tetheredtrust.com

Fit, compatibility and recall checks for AI agents before they buy: verdicts, evidence, receipts.

Runs in the cloudUpdated today
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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

Brotato Coach

A deterministic theorycrafter for Brotato, delivered as an MCP server you can chat with from Claude Code (and other MCP clients).

The design principle: a deterministic core holds the ground truth — weapon/item/character data, DPS formulas, stat mechanics — so the language model *looks facts up and computes* instead of recalling (and misremembering) them. Every tool returns a finished, verifiable answer or a structured error; there are no baked-in tier lists or opinions, only facts and math.

The dataset (data/brotato.json) is not committed — it is derived from copyrighted game files, so you build it yourself from a local Brotato install (see Building the dataset). A full build from Brotato 1.1.15.4 contains 202 weapons, 197 items, 50 characters, and 15 weapon-class sets.

Requirements

  • Python 3.11+
  • uv for environment/dependency management

Install dependencies:

uv sync

Quick start

Build the dataset (needs a local extraction — see Building the dataset), then start the server:

uv run python build_dataset.py                        # writes data/brotato.json

uv run python -m brotato_coach.server # starts the MCP server over stdio

The server refuses to start without data/brotato.json and tells you to build it first.

Run the tests (the dataset-dependent integration test is skipped when no dataset is built):

uv run pytest        # 89 tests (88 passed + 1 skipped without a built dataset)

Run

uvx spudcoach --data /path/to/brotato.json

The dataset is never distributed — build your own from your Brotato install: uv run python build_dataset.py (see docs/extraction-setup.md). Game version auto-detects from the decompiled recovered/singletons/progress_data.gd, and generated_at defaults to the current UTC time — pass --game-version/--generated-at explicitly to override either. SPUDCOACH_DATA works as an env-var alternative to --data.

Use as a Claude Code plugin

The MCP server is described by plugin/.mcp.json:

{

"mcpServers": { "spudcoach": { "command": "uv", "args": ["run", "python", "-m", "brotato_coach.server"], "cwd": "${CLAUDE_PLUGIN_ROOT}" } } }

The server reads the (locally built) data/brotato.json relative to its working directory, so it must run with the repository root as its `cwd` (the manifest handles this via ${CLAUDE_PLUGIN_ROOT} when bundled as a plugin), and you must build the dataset first.

To register it directly in Claude Code without packaging, add the server pointed at your checkout, e.g.:

claude mcp add spudcoach -- uv run --directory /path/to/spud-coach python -m brotato_coach.server

Once connected, just ask in natural language — the model routes your question to the tools below:

  • *"Does Handcuffs fit my Ranger run? I'm at 7 ranged damage, 65 HP."*
  • *"Minigun T4 vs Revolver T4 at 20 ranged damage — which hits harder?"*
  • *"Is attack speed ever dead weight? Can I let knockback go negative on a gun build?"*
  • *"What does the Ranger's ranged-damage bonus do to a raw stat of 6?"*
  • *"Here's my run.json — how's this build doing?"* (post-mortem a whole save at once)

Use with Claude Desktop

Claude Desktop can launch the server with uvx in two forms: fetch straight from this repo (auto-updates on restart, but needs git reachable — see the Windows note below), or point at a local checkout (nothing fetched at runtime; the most reliable form on Windows). Either way you supply your own locally built brotato.json — the dataset is never distributed.

  1. Install uv on the machine running Claude Desktop (winget install astral-sh.uv on Windows, or the standalone installer).
  2. Open the config file and add the spud-coach server:
  • Windows: %APPDATA%\Claude\claude_desktop_config.json
  • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json

Fetch-from-repo form:

   {

"mcpServers": { "spud-coach": { "command": "uvx", "args": [ "--from", "git+https://github.com/brendanlefebvre/spud-coach", "spudcoach", "--data", "C:\\Users\\ \\path\\to\\brotato.json" ] } } }

Point --data at your built dataset (SPUDCOACH_DATA works as an env-var alternative). On macOS use a POSIX path like /Users/ /brotato.json.

  1. Fully restart Claude Desktop (quit from the tray, not just close the window).
Windows: "Git executable not found" (or uvx not found)

The git+https://… form makes uv shell out to a git executable. Claude Desktop does not pass your shell — or even your System `PATH` — to the MCP subprocess; it spawns servers with its own trimmed environment. (The PATH it prints in the logs is its command-resolution list, *not* what the child process receives.) So a git that runs fine in PowerShell, installed in a System-PATH directory, can still come back "not found" here — and a bare "command": "uvx" can fail to resolve for the same reason. Two fixes:

  • Point at a local checkout — no runtime git (recommended). Clone once in a terminal where git works, then use --from instead of --from git+…:
  git clone https://github.com/brendanlefebvre/spud-coach C:\Users\<you>\src\spud-coach
  {

"mcpServers": { "spud-coach": { "command": "uvx", "args": ["--from", "C:\\Users\\ \\src\\spud-coach", "spudcoach", "--data", "C:\\Users\\ \\path\\to\\brotato.json"] } } }

Update later with git pull in that folder, then restart Desktop.

  • Or force the tools onto the server's `PATH`. Keep the git+https form and add an env block that hands the child an explicit PATH — git, plus uv's bin and the winget-links dir:
  "env": {

"PATH": "C:\\Program Files\\Git\\cmd;C:\\Users\\ \\.local\\bin;C:\\Users\\ \\AppData\\Local\\Microsoft\\WinGet\\Links;C:\\Windows\\System32" }

If uvx itself still isn't found, also set "command" to its absolute path (Get-Command uvx to locate it, e.g. C:\Users\ \AppData\Local\Microsoft\WinGet\Links\uvx.exe).

Available tools

All tools return a JSON object. Lookups that miss return {"error": "not_found", "did_you_mean": [...]}.

22 tools. Arguments marked ? are optional.

Start here
ToolArgumentsReturns
read_me—Session-start primer: how Brotato's core loop works, the source-verified stat mechanics, and what every precomputed field assumes. Call once, before anything else
Data lookups
ToolArgumentsReturns
get_weaponname, tier?Weapon record incl. raw stat-aware fields, on-hit effects, and weapon-class sets; {matches:[...]} if tier omitted and several tiers match
get_itemnameItem record: effects, tags, archetype, frozen_stat
get_characternameCharacter kit: wanted_tags, banned_item_groups, flat_bonuses, gain_modifiers, special_effects, class_bonuses, starting_weapon_pool
get_weapon_class_setclass_nameWeapon-class set bonuses (Blade, Gun, Elemental, …), by equipped count
list_weaponsscaling_stat?, tier?{weapons:[...]} filtered summaries
list_itemstag?, scaling_stat?, archetype?, tier?{items:[...]} filtered summaries
list_charactersscaling_stat?, wanted_tag?, banned_item_group?, special_effect?, class_bonus_set?, can_start_with?, detail?{characters:[...]} — full records, not summaries (see below)
get_filter_options—Valid filter values in the dataset: item tags, archetypes, scaling stats, tiers, weapon-class names, enemy abilities / attack kinds / zones, and the character filter vocabularies
DPS & comparison
ToolArgumentsReturns
weapon_dpsname, tier, stats, aoe_enemies_hit?, character?, weapon_count?, engagement_distance?, loadout?, apply_set_bonuses?Realized, stat-aware DPS at your build, split into base_dps + proc_dps, with a cadence breakdown and the assumptions baked in
compare_weaponsnames_with_tiers, stats, plus the same optional arguments as weapon_dps{ranking:[...]} sorted by DPS descending, at one shared stat block
compare_merge_pathsweapon_name, path_a, path_b, stats?Winner or crossover_rd for two tier-merge paths (lists of tiers)
stat_gradientweapons, stats, step?, character?, aoe_enemies_hit?, engagement_distance?Which stat to buy next: stats ranked by the DPS gain from +step of each. DPS only — survivability is out of scope
Build evaluation
ToolArgumentsReturns
evaluate_item_for_builditem_name, character_name, current_statsPer-effect verdict — live / wasted / harmful — with reasons, plus a summary
loadout_set_bonusesweapon_namesPer-class set progress across a whole loadout: equipped count, active bonuses, and next threshold
explain_statstatVerified stat mechanics: caps, special behavior, neglectable / never-negative flags
stat_display_valuecharacter, stat, raw_valueDisplayed value after the character's gain modifiers (e.g. Ranger RD 6 → 9)
Bestiary
ToolArgumentsReturns
get_enemyname, wave?Enemy record: base stats, per-wave stat slopes, attack profile, ability tags. Pass wave (1-20) to also resolve effective stats at that wave
list_enemiesappears_in?, ability?, attack_kind?{enemies:[...]} filtered summaries
wave_compositionwave, danger?Base-game (Crash Zone) composition for a wave: enemy groups, base counts, first-spawn timing, repeats
Run analysis & metadata
ToolArgumentsReturns
evaluate_runpath? or run_json?One-call post-mortem of a whole Brotato run.json save: run context (character, wave, danger), realized stats, weapon-DPS ranking, set progress, and per-item verdicts
check_dataset_version—game_version, generated_at, schema_version

Batch lookups. get_weapon, get_item and get_character accept name as either a string or a list of strings. A list returns {"results": [...]} in the order given, each entry a record or its own not_found — so detail on several entities costs one round-trip, not N.

`list_characters` returns full records, unlike list_weapons / list_items, which return summaries. The whole 50-character corpus is only ~7.7K tokens, so a survey answers in a single call with no follow-up get_character; pass detail="summary" for {id, name} rows instead. Its scaling_stat filter is a derived union — characters have no scaling-stat field — matching a positive stat-gain modifier, a positive flat bonus, or a matching wanted_tag. Each matched record carries a scaling_match object naming which signal fired, e.g. Engineer {"gain_pct": 25, "flat": 10, "wanted": true} vs Technomage {"wanted": true}, so the derivation is visible rather than asserted. Characters *penalised* in that stat are excluded from the match.

starting_weapon_pool is the run-start weapon-selection pool, not a fixed starting weapon: most characters offer a dozen or more, Arms Dealer offers only the Pistol,

Only the beginning is shown; read the rest in the repo

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