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abstract: 'We introduce [<span style="font-variant:small-caps;">21CMMC</span>]{}: a parallelized, Monte Carlo Markov Chain analysis tool, incorporating the epoch of reionization ([EoR]{}) seminumerical simulation [<span style="font-variant:small-caps;">21CMFAST</span>]{}. [<span style="font-variant:small-caps;">21CMMC</span>]{} estimates astrophysical parameter constraints from 21 cm [EoR]{} experiments, accommodating a variety of [EoR]{} models, as well as priors on model parameters and the reionization history. To illustrate its utility, we consider two different [EoR]{} scenarios, one with a single population of galaxies (with a mass-independent ionizing efficiency) and a second, more general model with two different, feedback-regulated populations (each with mass-dependent ionizing efficiencies). As an example, combining three observations ($z=8$, 9 and 10) of the 21 cm power spectrum with a conservative noise estimate and uniform model priors, we find that interferometers with specifications like the Low Frequency Array/Hydrogen Epoch of Reionization Array (HERA)/Square Kilometre Array 1 (SKA1) can constrain common reionization parameters: the ionizing efficiency (or similarly the escape fraction), the mean free path of ionizing photons and the log of the minimum virial temperature of star-forming haloes to within 45.3/22.0/16.7, 33.5/18.4/17.8 and 6.3/3.3/2.4 per cent, $\sim1 \sigma$ fractional uncertainty, respectively. Instead, if we optimistically assume that we can perfectly characterize the [EoR]{} modelling uncertainties, we can improve on these constraints by 