io.github.zazencodes/random-number-mcp

Official registry Other

Essential random number generation utilities from the Python standard library

Install

Add this to your client's MCP configuration (Claude Desktop: claude_desktop_config.json; Cursor: .cursor/mcp.json; VS Code and others use the same "mcpServers" shape).

PYPI package random-number-mcp
Claude Code
claude mcp add random-number-mcp -- uvx random-number-mcp==0.1.2
JSON configuration (Claude Desktop, Cursor, VS Code)
{
    "mcpServers": {
        "random-number-mcp": {
            "command": "uvx",
            "args": [
                "random-number-mcp==0.1.2"
            ]
        }
    }
}

Documentation

From the project's README on GitHub, refreshed weekly. Links open on GitHub.

Contents
  1. Random Number MCP
  2. Demo Video
  3. Tools
  4. Setup
  5. Tool Reference
  6. Security Considerations
  7. Development
  8. Testing with MCP Inspector
  9. MCP Registry
  10. License

Random Number MCP

Essential random number generation utilities from the Python standard library, including pseudorandom and cryptographically secure operations for integers, floats, weighted selections, list shuffling, and secure token generation.

Looking for the agent skill version? random-number-skills implements the same random number generation strategy as an agent skill instead of an MCP server.

Demo Video

https://github.com/user-attachments/assets/303a441a-2b10-47e3-b2a5-c8b51840e362

Tools

ToolPurposePython function
random_intGenerate random integersrandom.randint()
random_floatGenerate random floatsrandom.uniform()
random_choicesChoose items from a list (optional weights)random.choices()
random_shuffleReturn a new list with items shuffledrandom.sample()
random_sampleChoose k unique items from populationrandom.sample()
secure_token_hexGenerate cryptographically secure hex tokenssecrets.token_hex()
secure_random_intGenerate cryptographically secure integerssecrets.randbelow()

Setup

Claude Desktop

Add this to your Claude Desktop configuration file:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "random-number": {
      "command": "uvx",
      "args": ["random-number-mcp"]
    }
  }
}

Tool Reference

random_int

Generate a random integer between low and high (inclusive).

Parameters:

  • low (int): Lower bound (inclusive)
  • high (int): Upper bound (inclusive)

Example:

{
  "name": "random_int",
  "arguments": {
    "low": 1,
    "high": 100
  }
}
random_float

Generate a random float between low and high.

Parameters:

  • low (float, optional): Lower bound (default: 0.0)
  • high (float, optional): Upper bound (default: 1.0)

Example:

{
  "name": "random_float",
  "arguments": {
    "low": 0.5,
    "high": 2.5
  }
}
random_choices

Choose k items from a population with replacement, optionally weighted.

Parameters:

  • population (list): List of items to choose from
  • k (int, optional): Number of items to choose (default: 1)
  • weights (list, optional): Weights for each item (default: equal weights)

Example:

{
  "name": "random_choices",
  "arguments": {
    "population": ["red", "blue", "green", "yellow"],
    "k": 2,
    "weights": [0.4, 0.3, 0.2, 0.1]
  }
}
random_shuffle

Return a new list with items in random order.

Parameters:

  • items (list): List of items to shuffle

Example:

{
  "name": "random_shuffle",
  "arguments": {
    "items": [1, 2, 3, 4, 5]
  }
}
random_sample

Choose k unique items from population without replacement.

Parameters:

  • population (list): List of items to choose from
  • k (int): Number of items to choose

Example:

{
  "name": "random_sample",
  "arguments": {
    "population": ["a", "b", "c", "d", "e"],
    "k": 2
  }
}
secure_token_hex

Generate a cryptographically secure random hex token.

Parameters:

  • nbytes (int, optional): Number of random bytes (default: 32)

Example:

{
  "name": "secure_token_hex",
  "arguments": {
    "nbytes": 16
  }
}
secure_random_int

Generate a cryptographically secure random integer below upper_bound.

Parameters:

  • upper_bound (int): Upper bound (exclusive)

Example:

{
  "name": "secure_random_int",
  "arguments": {
    "upper_bound": 1000
  }
}

Security Considerations

This package provides both standard pseudorandom functions (suitable for simulations, games, etc.) and cryptographically secure functions (suitable for tokens, keys, etc.):

  • Standard functions (random_int, random_float, random_choices, random_shuffle): Use Python's random module - fast but not cryptographically secure
  • Secure functions (secure_token_hex, secure_random_int): Use Python's secrets module - slower but cryptographically secure

Development

Prerequisites
  • Python 3.10+
  • uv package manager
Setup
# Clone the repository
git clone https://github.com/example/random-number-mcp
cd random-number-mcp

# Install dependencies
uv sync --dev

# Run tests
uv run pytest

# Run linting
uv run ruff check --fix
uv run ruff format

# Type checking
uv run mypy src/
MCP Client Config
{
  "mcpServers": {
    "random-number-dev": {
      "command": "uv",
      "args": [
        "--directory",
        "<path_to_your_repo>/random-number-mcp",
        "run",
        "random-number-mcp"
      ]
    }
  }
}

Note: Replace <path_to_your_repo>/random-number-mcp with the absolute path to your cloned repository.

Building
# Build package
uv build

# Test installation
uv run --with dist/*.whl random-number-mcp
Release Checklist
  1. Update Version:
    • Increment the version number in pyproject.toml, src/random_number_mcp/__init__.py, and server.json.
  2. Update Changelog:
    • Add a new entry in CHANGELOG.md for the release.
      • Draft notes with coding agent using git diff context.
        Update the @CHANGELOG.md for the latest release.
        List all significant changes, bug fixes, and new features.
        Here's the git diff:
        [GIT_DIFF]
    • Commit along with any other pending changes.
  3. Create GitHub Release:
    • Draft a new release on the GitHub UI.
      • Tag release using UI.
    • The GitHub workflow will automatically build and publish the package to PyPI.

Testing with MCP Inspector

For exploring and/or developing this server, use the MCP Inspector npm utility:

# Install MCP Inspector
npm install -g @modelcontextprotocol/inspector

# Run local development server with the inspector
npx @modelcontextprotocol/inspector uv run random-number-mcp

# Run PyPI production server with the inspector
npx @modelcontextprotocol/inspector uvx random-number-mcp

MCP Registry

mcp-name: io.github.zazencodes/random-number-mcp

License

MIT License - see LICENSE file for details.

Frequently asked questions

What is io.github.zazencodes/random-number-mcp?

Essential random number generation utilities from the Python standard library

How do I install io.github.zazencodes/random-number-mcp?

It runs on your machine. In Claude Code: claude mcp add random-number-mcp -- uvx random-number-mcp==0.1.2. For other clients, paste the JSON configuration from this page into their MCP settings.

Does io.github.zazencodes/random-number-mcp need an API key?

Its registry entry lists no required key or secret. Some features may still need an account with the service it connects to.

Is io.github.zazencodes/random-number-mcp open source?

Yes. Its code is on GitHub under the MIT license.

Who maintains io.github.zazencodes/random-number-mcp?

It is published by zazencodes. AI.tn lists it but does not maintain or endorse it.

From the official MCP Registry. Listing is not an endorsement: review a server's code and permissions before giving it access to your data.