I have made a tool to derive statistics from a multiple alignment. It gives a score for each column of the multiple alignment given a substitution matrix. Here is the link (github) : MstatX. (use the -s trident option)

Hope it can help. If you need any help, just ask.

EDIT : The question "How to measure the conservation (or similarity) in a multiple alignment is quite difficult as it is discussed in these questions : Conservation Score Of Amino Acid Positions In Human Proteins and Entropy From A Multiple Sequence Alignment With Gaps

A first measure can be calculated by the following algorithm (the famous sum of pairs):

Msa msa;
float total = 0.0;
for (c = 0; c < nb_column; ++c) {
  float sum = 0.0;
  for (r = 0; r < nb_row - 1; ++r){
    for (s = r + 1; s < nb_row; ++s){
      sum += similarity_score(msa[c][r],msa[c][s]);
    }
  }
  total += sum / (nb_row *(nb_row -1) / 2);
}
total /= nb_column;

Where the similarity_score is your scoring matrix.

I think the answer is "no". The reason is that I cannot think of a meaningful way to define the % identity of a multiple sequence alignment.

If one defines it as as the fraction of aligned positions that are identical across all sequences, the % identity would automatically be lower the more sequences you have in the alignment. It would thus not be comparable between different alignments.

Depending on what you mean by 'measure of similarity'. PAM value if a protein alignment? Global %identity?

Look at Sean Eddy's tools. alistat, (build from the SQUID package) might meet your needs. It is also installed as part of the HMMER package.