developer-tools

Random.org

qianjue-cn

by qianjue-cn

Generate cryptographically secure random numbers with Random.org's RNG generator—perfect for key generation, sampling, a

Integrates with Random.org's API to generate cryptographically secure random data using atmospheric noise for applications requiring true randomness like cryptographic key generation, statistical sampling, and security testing.

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Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.

Uses atmospheric noise for true randomnessCryptographically secure random generationMultiple output formats supported

best for

  • / Cryptographic key generation and security testing
  • / Statistical sampling and research applications
  • / Developers needing true randomness over pseudorandom

capabilities

  • / Generate true random integers and sequences
  • / Create random decimal fractions and Gaussian distributions
  • / Generate cryptographically secure UUIDs
  • / Create random strings from custom character sets
  • / Generate random binary data in base64 or hex
  • / Monitor API usage statistics

what it does

Generates cryptographically secure random data using Random.org's atmospheric noise API. Provides true randomness for security applications, statistical sampling, and cryptographic operations.

about

Random.org is a community-built MCP server published by qianjue-cn that provides AI assistants with tools and capabilities via the Model Context Protocol. Generate cryptographically secure random numbers with Random.org's RNG generator—perfect for key generation, sampling, a It is categorized under developer tools.

how to install

You can install Random.org in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

license

MIT

Random.org is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

Random.org MCP Server

A Model Context Protocol (MCP) server that provides access to the api.random.org service for generating true random numbers, strings, UUIDs, and more.

Features

This MCP server provides the following tools:

  • generateIntegers - Generate true random integers within a specified range
  • generateIntegerSequences - Generate sequences of true random integers
  • generateDecimalFractions - Generate random decimal fractions between 0 and 1
  • generateGaussians - Generate random numbers from a Gaussian distribution
  • generateStrings - Generate random strings from specified characters
  • generateUUIDs - Generate true random UUIDs (version 4)
  • generateBlobs - Generate random binary data in base64 or hex format
  • getUsage - Get API usage statistics

Installation & Deployment

🚀 Quick Start with npm (Recommended)

Method 1: Global Installation

# Install globally
npm install -g random-org-mcp-server

# Verify installation
random-org-mcp --version

Method 2: Use without Installation

# Run directly with npx (no installation required)
npx random-org-mcp-server

Method 3: Local Project Installation

# Install in your project
npm install random-org-mcp-server

# Run from node_modules
npx random-org-mcp-server

🛠️ Build from Source

  1. Clone this repository:
git clone https://github.com/QianJue-CN/TRUERandomMCP.git
cd TRUERandomMCP
  1. Install dependencies:
npm install
  1. Build the project:
npm run build

Configuration

🔑 Get API Key

  1. Visit api.random.org to get a free API key
  2. Register and obtain your API key

⚙️ Configuration Methods

Method 1: Environment Variables (Recommended)

Create a .env file in your working directory:

# Copy example file (if building from source)
cp .env.example .env

Edit .env file:

RANDOM_ORG_API_KEY=your_api_key_here
RATE_LIMIT_REQUESTS_PER_SECOND=1
RATE_LIMIT_BURST_SIZE=5
REQUEST_TIMEOUT_MS=10000
MAX_RETRIES=3
RETRY_DELAY_MS=1000

Method 2: MCP Client Configuration

Configure directly in your MCP client (e.g., Claude Desktop):

{
  "mcpServers": {
    "random-org": {
      "command": "npx",
      "args": ["random-org-mcp-server"],
      "env": {
        "RANDOM_ORG_API_KEY": "your_api_key_here"
      }
    }
  }
}

Environment Variables

  • RANDOM_ORG_API_KEY (required) - Your api.random.org API key
  • RATE_LIMIT_REQUESTS_PER_SECOND (optional, default: 1) - Rate limiting
  • RATE_LIMIT_BURST_SIZE (optional, default: 5) - Burst size for rate limiting
  • REQUEST_TIMEOUT_MS (optional, default: 10000) - Request timeout in milliseconds
  • MAX_RETRIES (optional, default: 3) - Maximum number of retries
  • RETRY_DELAY_MS (optional, default: 1000) - Delay between retries

Usage

🔗 MCP Client Integration

Claude Desktop Configuration

  1. Locate your Claude Desktop configuration file:

    • Windows: %APPDATA%\Claude\claude_desktop_config.json
    • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
    • Linux: ~/.config/Claude/claude_desktop_config.json
  2. Add the Random.org MCP server configuration:

{
  "mcpServers": {
    "random-org": {
      "command": "npx",
      "args": ["random-org-mcp-server"],
      "env": {
        "RANDOM_ORG_API_KEY": "your_api_key_here"
      }
    }
  }
}
  1. Restart Claude Desktop

Alternative Configurations

Using Global Installation

{
  "mcpServers": {
    "random-org": {
      "command": "random-org-mcp",
      "env": {
        "RANDOM_ORG_API_KEY": "your_api_key_here"
      }
    }
  }
}

Using Local Installation

{
  "mcpServers": {
    "random-org": {
      "command": "node",
      "args": ["node_modules/random-org-mcp-server/dist/index.js"],
      "env": {
        "RANDOM_ORG_API_KEY": "your_api_key_here"
      }
    }
  }
}

Running the Server

🚀 Production Usage

If installed globally:

random-org-mcp

Using npx (no installation required):

npx random-org-mcp-server

From source:

npm start

🛠️ Development

For development with auto-reload:

npm run dev

Tool Examples

Generate Random Integers

{
  "name": "generateIntegers",
  "arguments": {
    "n": 5,
    "min": 1,
    "max": 100,
    "replacement": true,
    "base": 10
  }
}

Generate Random Strings

{
  "name": "generateStrings",
  "arguments": {
    "n": 3,
    "length": 8,
    "characters": "abcdefghijklmnopqrstuvwxyz0123456789",
    "replacement": true
  }
}

Generate UUIDs

{
  "name": "generateUUIDs",
  "arguments": {
    "n": 5
  }
}

Generate Gaussian Numbers

{
  "name": "generateGaussians",
  "arguments": {
    "n": 10,
    "mean": 0,
    "standardDeviation": 1,
    "significantDigits": 6
  }
}

Get Usage Statistics

{
  "name": "getUsage",
  "arguments": {}
}

API Limits

The api.random.org service has the following limits:

  • Integers: 1-10,000 numbers per request
  • Integer Sequences: 1-10,000 sequences, each 1-10,000 numbers long
  • Decimal Fractions: 1-10,000 numbers per request
  • Gaussians: 1-10,000 numbers per request
  • Strings: 1-10,000 strings per request, each 1-20 characters long
  • UUIDs: 1-1,000 UUIDs per request
  • Blobs: 1-100 blobs per request, each 1-1,048,576 bytes

Error Handling

The server includes comprehensive error handling:

  • Input validation for all parameters
  • Rate limiting to respect API limits
  • Automatic retries with exponential backoff
  • Detailed error messages for troubleshooting

Development

Scripts

  • npm run build - Build the TypeScript code
  • npm start - Run the compiled server
  • npm run dev - Run in development mode with auto-reload
  • npm run clean - Clean the build directory

Project Structure

src/
├── index.ts           # Main entry point
├── server.ts          # MCP server implementation
├── randomOrgClient.ts # API client for random.org
├── rateLimiter.ts     # Rate limiting implementation
├── config.ts          # Configuration management
└── types.ts           # TypeScript type definitions

License

MIT License - see LICENSE file for details.

Contributing

  1. Fork the repository
  2. Create a feature branch
  3. Make your changes
  4. Add tests if applicable
  5. Submit a pull request

Support

For issues related to this MCP server, please open an issue on GitHub. For api.random.org API issues, please refer to their documentation.

FAQ

What is the Random.org MCP server?
Random.org is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?
Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for Random.org?
This profile displays 30 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.5 out of 5—verify behavior in your own environment before production use.

Use Cases

Extended AI Capabilities

Add new capabilities to Claude beyond text generation

Example

Access external data sources, execute code, interact with tools and services

Transform Claude from chatbot to action-taking agent

Context Enhancement

Provide Claude with access to relevant context and data

Example

Load project documentation, access knowledge bases, query databases

Get more accurate, context-aware responses

Workflow Automation

Automate multi-step workflows combining AI and external tools

Example

Research → Summarize → Create document → Send notification

Complete complex tasks end-to-end without manual steps

Implementation Guide

Prerequisites

  • Claude Desktop 0.7.0+ or Cursor IDE with MCP support
  • Basic understanding of MCP architecture and capabilities
  • Access credentials for integrated services (if required)
  • Willingness to experiment and iterate on configuration

Time Estimate

15-60 minutes depending on server complexity

Installation Steps

  1. 1.Install MCP server: npm install -g [package-name] or via GitHub
  2. 2.Add server configuration to ~/.claude/mcp.json
  3. 3.Provide required credentials and configuration
  4. 4.Restart Claude Desktop to load new server
  5. 5.Test basic functionality with simple prompts
  6. 6.Explore capabilities and experiment with use cases
  7. 7.Document successful patterns for reuse

Troubleshooting

  • MCP server not loading: Check config syntax, verify installation
  • Connection errors: Check network, firewall, credentials
  • Feature not working: Read server docs, check required parameters
  • Performance issues: Monitor resource usage, check for network latency
  • Conflicts with other servers: Check port assignments, namespace collisions

Best Practices

✓ Do

  • +Read server documentation thoroughly before setup
  • +Start with simple use cases to validate functionality
  • +Test in non-production environment first
  • +Monitor resource usage and performance
  • +Keep servers updated for bug fixes and new features
  • +Document configuration for team members
  • +Use environment variables for sensitive configuration

✗ Don't

  • Don't grant overly permissive access to MCP servers
  • Don't skip reading security considerations in docs
  • Don't expose sensitive data without proper controls
  • Don't run untrusted MCP servers without code review
  • Don't ignore error messages—investigate root cause

💡 Pro Tips

  • Combine multiple MCP servers for powerful workflows
  • Create custom MCP servers for your specific needs
  • Share successful configurations with team
  • Use MCP inspector for debugging
  • Join MCP community for tips and troubleshooting

Technical Details

Architecture

Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.

Protocols

  • Model Context Protocol (MCP)
  • JSON-RPC 2.0
  • stdio or HTTP transport

Compatibility

  • Claude Desktop
  • Cursor IDE
  • Custom MCP clients

When to Use This

✓ Use When

Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.

✗ Avoid When

Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.

Integration

  • Tool composition: Chain multiple MCP tools in workflows
  • Context augmentation: Provide AI with relevant external data
  • Action delegation: Let AI execute tasks on external systems
  • Bidirectional sync: Keep AI context and external systems in sync

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.

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Ratings

4.530 reviews
  • Ava Brown· Dec 20, 2024

    Random.org is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • Sakshi Patil· Nov 11, 2024

    I recommend Random.org for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • William Wang· Nov 11, 2024

    Random.org reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

  • Chaitanya Patil· Oct 2, 2024

    Strong directory entry: Random.org surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • William Park· Oct 2, 2024

    Useful MCP listing: Random.org is the kind of server we cite when onboarding engineers to host + tool permissions.

  • Piyush G· Sep 25, 2024

    Random.org has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • Sakura Harris· Sep 21, 2024

    According to our notes, Random.org benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Ama Sanchez· Sep 21, 2024

    Random.org has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • Shikha Mishra· Aug 16, 2024

    According to our notes, Random.org benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Sakura Bhatia· Aug 12, 2024

    Random.org has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

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