Random.org▌
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.
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
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
- Clone this repository:
git clone https://github.com/QianJue-CN/TRUERandomMCP.git
cd TRUERandomMCP
- Install dependencies:
npm install
- Build the project:
npm run build
Configuration
🔑 Get API Key
- Visit api.random.org to get a free API key
- 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 keyRATE_LIMIT_REQUESTS_PER_SECOND(optional, default: 1) - Rate limitingRATE_LIMIT_BURST_SIZE(optional, default: 5) - Burst size for rate limitingREQUEST_TIMEOUT_MS(optional, default: 10000) - Request timeout in millisecondsMAX_RETRIES(optional, default: 3) - Maximum number of retriesRETRY_DELAY_MS(optional, default: 1000) - Delay between retries
Usage
🔗 MCP Client Integration
Claude Desktop Configuration
-
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
- Windows:
-
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"
}
}
}
}
- 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 codenpm start- Run the compiled servernpm run dev- Run in development mode with auto-reloadnpm 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
- Fork the repository
- Create a feature branch
- Make your changes
- Add tests if applicable
- 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.Install MCP server: npm install -g [package-name] or via GitHub
- 2.Add server configuration to ~/.claude/mcp.json
- 3.Provide required credentials and configuration
- 4.Restart Claude Desktop to load new server
- 5.Test basic functionality with simple prompts
- 6.Explore capabilities and experiment with use cases
- 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
4.5★★★★★30 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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