Pluggedin Random Number Generator

# Plugged.in Random Number Generator MCP Server A state-of-the-art cryptographically secure random number generator server implementing the Model Context Protocol (MCP). This server provides advanced random number generation capabilities for AI applications, LLMs, and other systems requiring high-quality randomness. ## 🚀 Features - **Cryptographically Secure**: Uses Node.js built-in `crypto` module for cryptographically secure pseudorandom number generation (CSPRNG) - **Multiple Data Types**: Generate integers, floats, bytes, UUIDs, strings, booleans, and random choices - **Flexible Configuration**: Customizable ranges, counts, encodings, and character sets - **MCP Compliant**: Full compatibility with Model Context Protocol specification including tools and prompts - **AI-Friendly Prompts**: Built-in prompt to help LLMs understand they should use this server for random generation - **Type Safety**: Written in TypeScript with comprehensive type definitions - **Error Handling**: Robust input validation and error reporting - **Performance Optimized**: Efficient algorithms suitable for high-throughput applications ## 📦 Installation ### Prerequisites - Node.js 18.0.0 or higher - npm or yarn package manager ### Install via Desktop Extension (DXT) For Claude Desktop users, you can install this server as a one-click Desktop Extension: 1. Download the latest `.dxt` file from the [releases page](https://github.com/VeriTeknik/pluggedin-random-number-generator-mcp/releases) 2. Open Claude Desktop 3. Go to Settings → Developer → MCP Servers 4. Click "Install from file" and select the downloaded `.dxt` file ### Install from npm ```bash npm install -g pluggedin-random-number-generator-mcp ``` Or install locally in your project: ```bash npm install pluggedin-random-number-generator-mcp ``` ### Deploy with Smithery Deploy this MCP server to the cloud using [Smithery](https://smithery.ai/): 1. Fork this repository 2. Connect your GitHub account to Smithery 3. Navigate to the Deployments tab 4. Click "Deploy" The server includes a `smithery.yaml` configuration file for easy deployment. ### Build from Source ```bash git clone https://github.com/VeriTeknik/pluggedin-random-number-generator-mcp.git cd pluggedin-random-number-generator-mcp npm install npm run build # Optional: Build DXT package npm run build:dxt ``` ## 🛠️ Usage ### Running the Server The server communicates via stdio (standard input/output) following the MCP protocol: ```bash # Using the built version node dist/index.js # Using development mode npm run dev ``` ### Integration with MCP Clients #### For npm installation (recommended): Add to your MCP client configuration. For Claude Desktop, add to your `claude_desktop_config.json`: ```json { "mcpServers": { "random-generator": { "command": "npx", "args": ["-y", "pluggedin-random-number-generator-mcp@latest"] } } } ``` This will always use the latest version from npm without requiring a global installation. #### For local installation: ```json { "mcpServers": { "random-generator": { "command": "node", "args": ["node_modules/pluggedin-random-number-generator-mcp/dist/index.js"] } } } ``` ## 🔧 Available Tools ### 1. Generate Random Integers Generate cryptographically secure random integers within a specified range. **Parameters:** - `min` (integer, optional): Minimum value (inclusive), default: 0 - `max` (integer, optional): Maximum value (inclusive), default: 100 - `count` (integer, optional): Number of integers to generate, default: 1, max: 1000 **Example:** ```json { "name": "generate_random_integer", "arguments": { "min": 1, "max": 100, "count": 5 } } ``` ### 2. Generate Random Floats Generate cryptographically secure random floating-point numbers. **Parameters:** - `min` (number, optional): Minimum value (inclusive), default: 0.0 - `max` (number, optional): Maximum value (exclusive), default: 1.0 - `count` (integer, optional): Number of floats to generate, default: 1, max: 1000 - `precision` (integer, optional): Decimal places to round to, default: 6, max: 15 **Example:** ```json { "name": "generate_random_float", "arguments": { "min": 0.0, "max": 1.0, "count": 3, "precision": 4 } } ``` ### 3. Generate Random Bytes Generate cryptographically secure random bytes in various encodings. **Parameters:** - `length` (integer, optional): Number of bytes to generate, default: 32, max: 1024 - `encoding` (string, optional): Output encoding ("hex", "base64", "binary"), default: "hex" **Example:** ```json { "name": "generate_random_bytes", "arguments": { "length": 32, "encoding": "hex" } } ``` ### 4. Generate UUIDs Generate cryptographically secure UUID version 4 identifiers. **Parameters:** - `count` (integer, optional): Number of UUIDs to generate, default: 1, max: 100 - `format` (string, optional): UUID format ("standard", "compact"), default: "standard" **Example:** ```json { "name": "generate_uuid", "arguments": { "count": 3, "format": "standard" } } ``` ### 5. Generate Random Strings Generate cryptographically secure random strings with customizable character sets. **Parameters:** - `length` (integer, optional): String length, default: 16, max: 256 - `charset` (string, optional): Character set ("alphanumeric", "alphabetic", "numeric", "hex", "base64", "ascii_printable"), default: "alphanumeric" - `count` (integer, optional): Number of strings to generate, default: 1, max: 100 **Example:** ```json { "name": "generate_random_string", "arguments": { "length": 12, "charset": "alphanumeric", "count": 2 } } ``` ### 6. Generate Random Choices Randomly select items from a provided list using cryptographically secure randomness. **Parameters:** - `choices` (array, required): Array of string items to choose from - `count` (integer, optional): Number of items to select, default: 1 - `allow_duplicates` (boolean, optional): Whether to allow duplicate selections, default: true **Example:** ```json { "name": "generate_random_choice", "arguments": { "choices": ["apple", "banana", "cherry", "date"], "count": 2, "allow_duplicates": false } } ``` ### 7. Generate Random Booleans Generate cryptographically secure random boolean values with configurable probability. **Parameters:** - `count` (integer, optional): Number of booleans to generate, default: 1, max: 1000 - `probability` (number, optional): Probability of true (0.0 to 1.0), default: 0.5 **Example:** ```json { "name": "generate_random_boolean", "arguments": { "count": 10, "probability": 0.7 } } ``` ## 🤖 AI Prompts The server includes a built-in prompt to help LLMs understand they should use this server for random number generation rather than attempting to generate random values themselves. ### Available Prompt: `generate_random` This prompt educates the AI about its limitations in generating random numbers and guides it to use the available cryptographically secure tools. **Parameters:** - `type` (string, optional): Type of random value needed (integer, float, uuid, string, bytes, choice, boolean) - `requirements` (string, optional): Specific requirements for the random generation **Example Usage:** When an LLM receives a request like "Generate a random password" or "Pick a random number", the prompt will: 1. Acknowledge that LLMs cannot generate truly random values 2. Explain the available cryptographically secure tools 3. Guide the AI to use the appropriate tool for the task This ensures that all random generation in your application uses proper cryptographic methods rather than predictable AI-generated patterns. ## 🔒 Security Features This server implements several security best practices: - **Cryptographically Secure Randomness**: All random number generation uses Node.js `crypto` module functions (`randomBytes`, `randomInt`, `randomUUID`) which provide cryptographically secure pseudorandom numbers suitable for security-sensitive applications. - **Input Validation**: Comprehensive validation of all input parameters to prevent injection attacks and ensure data integrity. - **Rate Limiting**: Built-in limits on generation counts to prevent resource exhaustion attacks. - **Error Handling**: Secure error messages that don't leak sensitive information about the system state. ## 🧪 Testing The server includes a comprehensive test suite that validates all functionality: ```bash # Run the test suite node test.js ``` The test suite covers: - Tool discovery and listing - All random generation functions - Input validation and error handling - Output format verification - Statistical properties validation ## 📊 Performance The server is optimized for performance while maintaining security: - **Efficient Algorithms**: Uses optimized native crypto functions - **Memory Management**: Minimal memory footprint with efficient buffer handling - **Concurrent Requests**: Thread-safe design supporting multiple simultaneous requests - **Scalability**: Suitable for high-throughput applications ## 🔧 Development ### Project Structure ``` pluggedin-random-number-generator-mcp/ ├── src/ │ └── index.ts # Main server implementation ├── dist/ # Compiled JavaScript output ├── test.js # Comprehensive test suite ├── package.json # Project configuration ├── tsconfig.json # TypeScript configuration └── README.md # This documentation ``` ### Building ```bash npm run build ``` ### Development Mode ```bash npm run dev ``` ### Testing with MCP Inspector You can test the server using the MCP Inspector tool: ```bash npm run inspector ``` This will start the MCP Inspector web interface where you can: - View available tools - Test tool execution - Inspect request/response payloads - Debug server behavior ## 🤝 Contributing Contributions are welcome! Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change. ### Development Guidelines 1. Follow TypeScript best practices 2. Maintain comprehensive test coverage 3. Update documentation for new features 4. Ensure all tests pass before submitting 5. Follow semantic versioning for releases ## 📄 License This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details. ## 🔗 Related Projects - [Model Context Protocol](https://modelcontextprotocol.io/) - The official MCP specification - [Plugged.in](https://plugged.in/) - MCP server management and discovery platform - [MCP SDK](https://github.com/modelcontextprotocol/typescript-sdk) - Official TypeScript SDK for MCP ## 📞 Support For support, questions, or feature requests: - Open an issue on [GitHub](https://github.com/VeriTeknik/pluggedin-random-number-generator-mcp/issues) - Visit the [Plugged.in platform](https://plugged.in/) for MCP server management - Check the [MCP documentation](https://modelcontextprotocol.io/docs) for protocol details