In the last decade, GPS collars have increasingly been used in Mediterranean agro-silvopastoral farms, especially when animals graze unsupervised in large surface areas of rangeland, with or without fences. Farmers’ interest is mainly to reduce the time spend finding and gathering the animals and eventually to identify off-limit behaviours or predation; however, GPS tracks can be analyzed further and provide other useful information. In the P@stor-all project, we explored ways to exploit the tracks recorded with GPS collars to provide operational indicators for decision making in pastoral contexts. Our main objective was to describe the spatial behavior of the flock in terms of both occupation of the rangeland and grazing effort for the animals. The indicators should interest the farmers and be suited to “real life” conditions. Seven farmers participated to the P@stor-all project, representing a variety of agro-silvo-pastoral systems and were trusted with a GPS collar, to be deployed in their flock. The frequency of data acquisition was set at 5 min, in order to strike a balance between the accuracy of data acquisition and the feasibility of recharging the batteries. The GPS tracks were recorded in various seasons, grazing conditions and locations. Based on the characteristics of the collected data and the associated free satellite data, but also on repeated interviews with the farmers, we proposed and calibrated a set of 7 indicators: area explored by the flock, occupation density, daily distance covered by the flock, instant speed along the grazing route and daily total ascent. In the P@stor-all platform, each farmer may visualize these various indicators, together with basic information about calculation methods, sensitivity to the quality of GPS data, and suggestions of interpretation. A variety of indicators is needed to account for the diversity of grazing contexts: depending on the farm and season, different indicators might be meaningful to adjust the grazing management. The absolute values and relative changes in each indicator also depend on the local conditions, thus each farmer will need to build his own local references and make his own decisions.