Jonatan,
You can find the SAS macro for the adjusted Scott-Knott in the link from this paper
http://ref.scielo.org/n4c75n
About the widespread use of it in Brazil, you should understand that the test by itself was proposed as an alternative to avoid ambiguity (which should not be understood as issue in comparison tests since "comparison tests were created to detect differences" - Tukey).
The Scott-Knott test was developed by two economics professors from Auckland and London and was very criticized by american researchers in the very beginning because it does not control the experiment-wise Type I Error as the MCP if there are more than a cluster of means (which means it does control it only if there is no true difference among them or if all the means are truly different). Also be aware that this statment is validy if you do evaluated the Scott-Knott test in the same manner as the MCP are, which is not the best approach since they different goals.
It is an alternative for a post ANOVA analysis, but it has a different concept than Tukey, Duncan, SNK, Dunett and my others.
Despite the lack of the control of the experiment-wise error, the Scott-Knott test has a much higher power than those listed above, since the most of MCPs lowers a lot the "real" Type I Error to guarantee it do not surpass the nominal level, therefore they have high Type II Error, which can be understood as low Power.
Thus, in a scenario were the Type I Error is not a big concern, the Scott-Knott (1974) it is a good option (i.e. preliminary experiments or studies where it is expected to have many treatments in the same cluster and it is not interesting to carry all of them to the next research stage if they show No Significant Difference. It is good fit for researches areas where there are a high number of treatments with such small variation among those and it is possible to perform a following validation, these scenarios are indeed rare if you take in account the multiple areas where statistics play a big role. I notice a lot of use of this test in agronomic research, but almost never in the other areas, so if you take in account that Brazil is country that play big almost only in agriculture it is possible to understand the wide adoption of the test in Brazil.
Regards,
