Large language models often struggle to generate truly random numbers, exhibiting biases that can impact applications requiring genuine unpredictability. This tool addresses that limitation by acting as a Model Context Protocol (MCP) server, providing access to high-quality random numbers sourced from atmospheric noise via random.org. It helps developers ensure their LLM-driven applications have access to unbiased randomness for critical functions.