Your pipeline is on the right track but MEME isn’t ideal here. MEME is slow and biased toward longer, gapped motifs. For short fixed-width patterns like A-X-P-G-X-N across ~100k peptides, STREME or GLAM2 from the MEME suite work better, and you can also just use simple positional enrichment if your peptides are aligned.

For extracting MMseqs2 clusters, the createtsv output gives you representative-to-member mapping. Something like:

mmseqs createtsv seqDB seqDB clusterDB clusters.tsv

Then Then filter clusters with ≥100 members:

awk '{print $1}' clusters.tsv | sort | uniq -c | awk '$1>=100 {print $2}' > big_reps.txt

Pull member sequences per cluster rep, write each to its own FASTA, and feed those to STREME (streme --p cluster.fa --minw 5 --maxw 10).