io.github.zazencodes/random-number-mcp
Essential random number generation utilities from the Python standard library
Installation
Ajoutez ceci à la configuration MCP de votre client (Claude Desktop : claude_desktop_config.json ; Cursor : .cursor/mcp.json ; VS Code et les autres utilisent la même forme « mcpServers »).
random-number-mcpclaude mcp add random-number-mcp -- uvx random-number-mcp==0.1.2
{
"mcpServers": {
"random-number-mcp": {
"command": "uvx",
"args": [
"random-number-mcp==0.1.2"
]
}
}
}
Documentation
Tirée du README du projet sur GitHub, actualisée chaque semaine. Les liens ouvrent GitHub.
Sommaire
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
| Tool | Purpose | Python function |
|---|---|---|
random_int | Generate random integers | random.randint() |
random_float | Generate random floats | random.uniform() |
random_choices | Choose items from a list (optional weights) | random.choices() |
random_shuffle | Return a new list with items shuffled | random.sample() |
random_sample | Choose k unique items from population | random.sample() |
secure_token_hex | Generate cryptographically secure hex tokens | secrets.token_hex() |
secure_random_int | Generate cryptographically secure integers | secrets.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 fromk(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 fromk(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'srandommodule - fast but not cryptographically secure - Secure functions (
secure_token_hex,secure_random_int): Use Python'ssecretsmodule - 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
- Update Version:
- Increment the
versionnumber inpyproject.toml,src/random_number_mcp/__init__.py, andserver.json.
- Increment the
- Update Changelog:
- Add a new entry in
CHANGELOG.mdfor the release.- Draft notes with coding agent using
git diffcontext.
Update the @CHANGELOG.md for the latest release. List all significant changes, bug fixes, and new features. Here's the git diff: [GIT_DIFF] - Draft notes with coding agent using
- Commit along with any other pending changes.
- Add a new entry in
- 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.
- Draft a new release on the GitHub UI.
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.
Questions fréquentes
Qu'est-ce que io.github.zazencodes/random-number-mcp ?
Essential random number generation utilities from the Python standard library
Comment installer io.github.zazencodes/random-number-mcp ?
Il s'exécute sur votre machine. Dans Claude Code : claude mcp add random-number-mcp -- uvx random-number-mcp==0.1.2. Pour les autres clients, collez la configuration JSON de cette page dans leurs réglages MCP.
Faut-il une clé API pour io.github.zazencodes/random-number-mcp ?
Son entrée au registre n'indique aucune clé ni secret obligatoire. Certaines fonctions peuvent tout de même demander un compte auprès du service auquel il se connecte.
io.github.zazencodes/random-number-mcp est-il open source ?
Oui. Son code est sur GitHub sous licence MIT.
Qui maintient io.github.zazencodes/random-number-mcp ?
Il est publié par zazencodes. AI.tn le référence sans le maintenir ni le recommander.
Issu du registre MCP officiel. Être listé n'est pas une recommandation : vérifiez le code et les permissions d'un serveur avant de lui donner accès à vos données.