Similar to memristors, memcapacitors are capacitors whose capacitance depends on the history of their input voltage, exhibiting a q-v characteristic defined by a closed-pinched hysteresis loop, where q=0 whenever v=0 (and vice versa) [1]. Contrary to memristors, whose solid-state implementations have experienced a significant progress over the past decade [2], the availability of solid-state memcapacitors remains more limited. Because of that, most current memcapacitors rely on circuit emulators based on silicon-CMOS technology, which typically incorporate a memristor emulator to mutate its behavior to that of a memcapacitor. This is a useful interim approach to explore the potential of these devices while awaiting technologically viable solid-state implementations of memcapacitors, as demonstrated in various applications including adaptive filters, chaotic circuits, and neuromorphic computing. However, these emulators are based on components designed to reproduce a deterministic behavior, thus lacking the inherent variability of real memcapacitors, which can be beneficial for introducing randomness and adaptability into implementations [3]. Therefore, the incorporation of memristors into memcapacitor emulators can introduce such variability and potentially unlock new functionalities beyond those of a purely deterministic system. This latter feature is paramount for mimicking the stochastic nature of biological synapses or generating high-entropy random sequences [4]. In this context, this work presents the implementation of a memcapacitor emulator by transforming a commercial Self-Directed-Channel (SDC) tungsten-doped memristor (Knowm Inc., NM, USA) into a memcapacitor. This mutator relates the memcapacitance with the Miller effect, generated by a capacitor in the feedback loop of a memristance-dependent-gain amplifier [5], as shown in Fig. 1. The feasibility of the proposed emulator was demonstrated through LTspice simulations using the experimental characteristics of the memristor, as well as through an experimental implementation. The results demonstrate that, until solid-state memcapacitors become widely available, using solid-state memristors in memcapacitor emulators is the key to explore more realistic memcapacitor implementations and their potential across multiple applications.