Increased interest in holistic soil management is driving a demand for analytical approaches to assessing soil health that integrate biological and physical assessment of soils with chemical analyses. In the Global North, there is an expanding interest among farmers to engage in measuring and evaluating soil nutrient status and soil health. There is also a need for on-site soil testing in developing regions of the Global South, where access to quality soil testing services is often limited. Here, I report research results on measuring soil biological activity, specifically, assessing soil microbial biomass carbon (SMB-C) using a recently developed, rapid, on-site testing tool called microBIOMETER® (Prolific Earth Sciences, Inc., Montgomery, NY, USA). Soil samples were taken from cover crop trials established at two sites in New York, the Hudson Valley Farm Hub (Farm Hub) and Cornell Musgrave Research Farm (Musgrave). Results of SMB-C from use of the microBIOMETER® were compared to the following soil health assays: chloroform fumigation-extraction (CFE), chloroform fumigation-incubation (CFI), soil respiration, permanganate oxidizable carbon (active carbon), and autoclaved citrate extractable soil protein (soil protein). For each location, a Pearson’s correlation analysis was used to explore linear relationships between the laboratory soil health assays and the microBIOMETER®. Multivariate linear regression was used to compare the microBIOMETER® results to the other soil health assays to account for effects of cover crop treatments and location. Active carbon and soil respiration were significantly correlated at both the Farm Hub, r=0.73 (p<0.0001) and at Musgrave, r=0.55 (p=0.0055). At the Farm Hub, active carbon was also significantly correlated with soil protein (r=0.64, p=0.0008) and the microBIOMETER® (r=0.43, p=0.0343). As anticipated, there was a significant correlation between CFE and CFI at the Farm Hub (r=0.65, p=0.0048). In the multivariate modeling, location was significant, but treatment (cover crops planted) and the treatment-location interaction were not significant in all models. Multivariate models with microBIOMETER® as the response variable and location with one soil health assay as explanatory variables were fit. Of the five soil health assays tested, soil protein was significantly related to microBIOMETER® (p=0.0453) and active carbon was significant at p=0.0829. There was no evidence of a significant relationship between microBIOMETER® and the other three soil biological assays. The results of this study indicate that the microBIOMETER® tool is reflecting some aspects of soil biological health, but that further research is needed to understand more precisely how useful this tool will be as a soil health indicator. While the microBIOMETER® is easy to use and affordable, its use as a soil health test for agroecosystem management is unclear.