Fair Dice

Dice an AI game master can't cheat with. Before each roll, the model has to say what's at stake. The dice then decide the result, and the model can't re-roll.

When a language model narrates the outcome of your character's action, it decides by itself whether you succeed, and it tends to let you. Fair Dice takes that decision away from it:

• resolve_action: 2d6 for an uncertain action. Before rolling, the model declares what a partial success costs and what a failure brings. 10+ is a clean success, 7–9 is success with the declared cost, 6 or less is failure with the declared trouble.

• ask_oracle: a d100 yes/no answer about the world ("Is the gate guarded?"), rolled against a likelihood the model sets from the facts first. The extreme ends become "yes, and" / "no, and".

• roll_dice: plain dice notation for damage, tables and counts: 3d6, 2d8+3, 4d6kh3, 2d20kl1.

The model never chooses the numbers or the target. The server rolls with a cryptographic random generator and returns the outcome band itself. If the model asks about the same action or question again within 20 minutes, it gets the original result back. Every roll appears as a tool call in your chat.

It works in any app that supports MCP servers: LibreChat, Claude Desktop, Claude Code, Cursor, VS Code and others. There is also a SillyTavern version.

Two ways to play

In apps that read MCP server instructions (LibreChat with serverInstructions: true, Claude Desktop, Claude Code), the server passes the chosen mode's rules to the model by itself. In other apps, add the rules as a skill or paste them into your system prompt (see Skills and prompts).

Related MCP server: mcp-randoom

Install

All setups need Node.js 18 or newer, except Claude Desktop, which brings its own.

LibreChat

Add this to librechat.yaml and restart LibreChat:

mcpServers:
  fair-dice:
    type: stdio
    command: npx
    args: ["-y", "fair-dice-mcp"]
    serverInstructions: true
    chatMenu: true
    initTimeout: 60000

For a roll on every prompt, add env: { FAIR_DICE_MODE: every-prompt }. Then pick Fair Dice in the chat's MCP menu, or add its tools to an agent in the Agent Builder. The Docker image already has Node, so this works there too. The first start takes a little longer while npx downloads the package.

Claude Desktop

Download fair-dice.mcpb from the latest release and double-click it, or install it from Settings → Extensions. The mode, the memory window and an optional log file can be set on the extension's settings page.

Claude Code

claude mcp add fair-dice -- npx -y fair-dice-mcp

For every-prompt mode, add -e FAIR_DICE_MODE=every-prompt before the --. On native Windows (not WSL), use cmd /c npx in place of npx.

Cursor, VS Code, Cline, Windsurf and other MCP apps

Most apps take the same JSON block:

{
  "mcpServers": {
    "fair-dice": {
      "command": "npx",
      "args": ["-y", "fair-dice-mcp"],
      "env": { "FAIR_DICE_MODE": "gm" }
    }
  }
}

Without npm

npx can also run the server straight from GitHub. Use "args": ["-y", "github:LROsocha-design/fair-dice-mcp"] in any of the setups above, or clone it:

git clone https://github.com/LROsocha-design/fair-dice-mcp
cd fair-dice-mcp
npm install

Then use node with the full path to server.cjs as the command in any of the setups above.

Settings

Each setting can be an environment variable or a command-line flag (--mode every-prompt).

The re-roll memory belongs to the server process. LibreChat runs one process for all its users, so two users who describe the exact same action within the window would get the same result.

Skills and prompts

The rules for both modes also come as Agent Skills and as plain text:

Claude Desktop and Claude Code also offer both rule sets as MCP prompts (fair-dice-gm, dice-every-prompt), which you can attach to a chat from the prompt menu.

The skills need the dice tools. Without them, the model is told not to invent a roll. It either decides from the facts, or uses a 2d6 result you paste in yourself.

How fair is it?

• The model can only describe the attempt and the stakes. It never chooses dice or targets, and the band comes back from the server already decided.

• A modifier is limited to −2…+2 and is refused without a stated reason.

• Asking again about the same action or question (ignoring case and punctuation) returns the first result.

• Over 3,000 test rolls, the three bands came out within a point of the expected 16.7% / 41.7% / 41.7%. npm test repeats this check.

What it can't stop: a model can still write a different outcome than the one rolled. In practice this is rare. In one long roleplay campaign, 69 of 73 failed rolls that could be checked were written as rolled, 3 were softened, and none were turned into a success. The FAIR_DICE_LOG file lets you check your own games.

Development

npm install
npm test
python tools/build.py

npm test runs the server through a real MCP client: every tool, the modes, the re-roll memory, logging, and the odds. tools/build.py writes the skill files and zips and the Claude Desktop bundle, and checks the repo for leftover personal paths. It needs Python, plus Pillow for the icon.

License

MIT