The detection and subsequent characterisation of exoplanets are intimately linked to the characteristics of their host star. Therefore, it is necessary to study the star in detail in order to understand the formation history and characteristics of their companion(s). Our aims were to develop a community tool that allows the automated calculation of stellar parameters for a large number of stars, using high resolution echelle spectra and minimal photometric magnitudes, and introduce the first results in this work. We measured the equivalent widths of several iron lines and used them to solve the radiative transfer equation assuming local thermodynamic equilibrium to obtain the atmospheric parameters ($T_{text{eff}}$, [Fe/H], logg and $xi_t$). We used these values to derive the abundance of 11 chemical elements in the stellar photosphere (Na, Mg, Al, Si, Ca, Ti, Cr, Mn, Ni, Cu and Zn). Rotation and macroturbulent velocity were obtained using temperature calibrators and synthetic line profiles to match the observed spectra of five absorption lines. Finally, by interpolating in a grid of MIST isochrones, we derived the mass, radius and age using a Bayesian approach. SPECIES obtains bulk parameters that are in good agreement with measured values from different existing catalogues, including when different methods are used to derive them. We find excellent agreement with previous works that used similar methodologies. We find discrepancies in the chemical abundances for some elements with respect to other works, which could be produced by differences in $T_{text{eff}}$, or in the line list or the atomic line data used to derive them. We also obtained analytic relations to describe the correlations between different parameters, and we implemented new methods to better handle these correlations, which provides a better description of the uncertainties associated with the measurements.
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