# Dice Roll

> Use this tool when you need to generate random outcomes or simulate chance events, such as determining probabilities or making decisions based on randomness. The Dice Roll tool solves problems like modeling uncertain events or creating games of chance by accepting parameters for dice faces and rolls, and returning individual and summed results. It is ideal for use cases requiring quick, randomized outcomes with validated input and output through the MCP stdio transport.

Canonical page: https://skillsregistry.net/skills/dice-roll  
JSON: https://api.skillsregistry.net/v1/skills/dice-roll

## Description

A simple dice rolling MCP server that provides a tool for generating random dice rolls. The server implements a single tool called 'roll_dice' that accepts parameters for the number of faces on the dice and how many times to roll, returning both individual roll results and their sum. It uses the Model Context Protocol's stdio transport for communication and is built with TypeScript, leveraging the Zod library for input validation and schema generation.

## Trust

- **Trust score (0–1):** 0.65
- **Verification tier:** scanned
- **Last scanned:** 2026-09-02

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-09-02

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/dice-roll)
- **Repository:** <https://github.com/shimapon/mcp-server-diceroll>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "dice-roll"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/dice-roll` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/dice-roll/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt