I've done what you're attempting with the Tiger road data, so it stands to reason it would work for what you're doing here. The bold value in this filename (the last one in your list, above)..
..is a so-called FIPS code. Specifically, this one is Coconino County, AZ. So all you need is something that provides a nice list of FIPS codes, then you can write a fun one-off program to concatenate URLS for each FIPS code, then download the corresponding tiger file.
In my case, I got the corresponding Tiger US counties shapefile (use the same year as your other data so the FIPS have the best 1-to-1 match), then I used Python and the OGR bindings to iterate over my shapefile and concat together a url for each county record in the shapefile, then download them one at a time (I further used ogr2ogr calls in the same automation to ingest each download into MySQL so it all happened in the same pass).
It was pretty cool. And this probably goes without saying, but you should test against only a few features, then once you have the kinks worked out, run the whole thing overnight.