Advanced Model Context Protocol server delivering high-quality, hardware-entropy-based random values for AI applications, supporting dice rolls, random ranges, and statistical variates ideal for simulations, modeling, and game mechanics.
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FortunaMCP is an advanced MCP server dedicated to generating high-quality random values. It leverages the Fortuna C-extension, which is directly powered by Storm—a robust, thread-safe C++ RNG engine optimized for high-speed, hardware-based entropy. FortunaMCP provides dependable randomness for a wide range of AI applications.
Large language models excel at natural language processing but rely on deterministic algorithms that fall short when true unpredictability is required. In contrast, FortunaMCP delivers genuine randomness. This capability makes it indispensable for scenarios where unbiased, unpredictable outcomes are critical, and where LLM approximations (hallucinations) simply won’t suffice.
FortunaMCP is perfectly suited for tasks like Monte Carlo simulations, complex system modeling and analysis, and interactive game mechanics. It is not intended for blockchain, security or encryption oriented tasks.
Fortuna.dice(rolls=3, sides=6)
Fortuna.random_range(start=10, stop=100, step=5)
Fortuna.bernoulli_variate(ratio_of_truth=0.7)
Fortuna.binomial_variate(number_of_trials=20, probability=0.5)
Fortuna.negative_binomial_variate(number_of_trials=5, probability=0.4)
Fortuna.geometric_variate(probability=0.25)
Fortuna.poisson_variate(mean=4.0)
[lower_limit, upper_bound)
. Both bounds are within the float limits of -1.7976931348623157e+308 to 1.7976931348623157e+308.Fortuna.random_float(lower_limit=0.0, upper_bound=1.0)
Fortuna.triangular(lower_limit=10.0, upper_limit=100.0, mode=50.0)
Fortuna.beta_variate(alpha=2.0, beta=5.0)
Fortuna.pareto_variate(alpha=1.5)
Fortuna.vonmises_variate(mu=0.0, kappa=1.0)
Fortuna.exponential_variate(lambda_rate=0.5)
Fortuna.gamma_variate(shape=2.0, scale=3.0)
Fortuna.weibull_variate(shape=1.5, scale=100.0)
Fortuna.normal_variate(mean=0.0, std_dev=1.0)
Fortuna.log_normal_variate(log_mean=0.0, log_deviation=1.0)
Fortuna.extreme_value_variate(location=0.0, scale=1.0)
Fortuna.chi_squared_variate(degrees_of_freedom=5.0)
Fortuna.cauchy_variate(location=0.0, scale=1.0)
Fortuna.fisher_f_variate(degrees_of_freedom_1=5.0, degrees_of_freedom_2=10.0)
Fortuna.student_t_variate(degrees_of_freedom=10.0)
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