Random Number MCP provides a compact suite of random-number utilities drawn from Python's standard library. It exposes both fast, non-cryptographic operations and cryptographically secure alternatives, enabling LLMs to generate numbers, select or shuffle items, and create tokens in deterministic workflows while keeping cryptographic security where needed. The server implements these functions as named tools: random_int (generate a random integer), random_float (generate a random float), random_choices (select k items with optional weights), random_shuffle (return a shuffled copy), random_sample (select k unique items without replacement), secure_token_hex (cryptographically secure hex tokens), and secure_random_int (cryptographically secure integers below an upper bound). Each tool maps to the corresponding Python stdlib function (random.randint, random.uniform, random.choices, random.sample, secrets.token_hex, secrets.randbelow). The package distinguishes between standard and secure functions: standard for simulations and general use; secure for tokens and keys. It is designed for developers and testers integrating RNG capabilities into MCP-driven workflows, with setup guidance and MCP client configuration examples included.