Toxin-producing cyanobacteria blooms in surface waters are becoming more prevalent around the world. Moreover, they are increasingly occurring in more northern regions of Europe. Rising global temperatures, extreme weather events, and human-caused eutrophication of water bodies contribute to these increases in bloom occurrences. Multiple uses of potentially contaminated surface water, like crop irrigation, fresh and brackish water fisheries, and water for livestock, are not included in the current limited legislation concerning cyanotoxin presence in water. Therefore, toxin accumulation through these activities might occur in these foods and thus reach the human food chain. While cyanotoxins have been observed throughout these exposure pathways, reliable data are too scarce to perform a proper risk assessment. Moreover, some of the available data was obtained with methods not validated for the application they were being used for. The presence of toxins can usually be ascertained from the results, but the reliability of the toxin quantification is insufficient. A lack of proper reference materials (RM) for cyanotoxins in diverse matrices contributes to the lack of proper quality assurance, as such RM could be used to verify analytical approaches. To close these knowledge gaps, multiple analytical methods were developed and validated by Sciensano under ISO 17025 accreditation. Specifically, methods were set up for the quantification of cyanotoxins in water, food supplements, fruits and vegetables, milk and freshwater fish. Moreover, these methodologies were further employed to quantify toxins during monitoring and research activities concerning the different matrices. Additionally, progress was made to produce RM for cyanotoxins in plant tissues by growing crops in hydroculture using cyanotoxin-contaminated water. Major results from our monitoring efforts were the presence of cyanotoxins in food supplements, freshwater fish, and crop samples. Moreover, we provided data on crop and irrigation type-dependent accumulation of cyanotoxins in fruits and vegetables. Furthermore, this data was valorized by active method optimization for the development of RM for cyanotoxins in fruits and vegetables. Indeed, cyanotoxins are present in most tested matrices, and production of RM should be possible in the future. However, loads of work is still necessary to be able to cover the wide range of cyanotoxins, pertinent unresolved data gaps, and provide sufficient monitoring data to make an accurate health risk assessment.