Hi, Neha-

Yes, correct.

Note, though, that an additional important piece of information is how you want the warping between the anatomical volume and the template volume to be calculated: with linear affine or with nonlinear warping? The former is default in the program (because it takes a lot less time, and so is more convenient in teaching circumstances), but the latter is what we strongly recommend for real analyses. So, while you are "getting to know" afni_proc.py, it might be fine to just use linear affine alignment to the template (that is what we use during the Bootcamp, for example, for the sake of time), but then you might want to consider using our current recommendation: @SSwarper to perform both skullstripping (the "SS" part of the name) and nonlinear warping to a template-- for this program, you have to use one of a set of templates versions we have made from standard templates:
+ MNI152_2009_template_SSW.nii.gz
+ TT_N27_SSW.nii.gz
+ HaskinsPeds_NL_template1.0_SSW.nii.gz
.... but you seem to want MNI, anyways. The outputs of this program then get input to afni_proc.py, as described in the programs' help file.

And actually, for a comparison (plus methodology on how to combine the programs), you can look to the most recent Bootcamp dataset: in AFNI_data6/FT_analysis/, there are two particular scripts for afni_proc.py:
s05.ap.uber : example single subject analysis with linear affine registration to a template (-> what we run in class, takes about 10mins to run)
s05.ap.uber.NL : same as s05.ap.uber *but* with nonlinear warping to a template, using results from @SSwarper, which was run in the manner shown in AFNI_data6/FT_analysis/Qwarp/s00.warper

--pt