Are these available currently or soon?

You can use a wrapper function to evaluate an mxAlgebra across all rows. For example, assume I need to evaluate the algebra A + B + C, and my data set has N rows. Then I would use,

evalWrapper <- function(expression, model, rows) {
    expression <- match.call()$expression
    lapply(rows, function(x) { eval(substitute(mxEval(exp, model, compute=TRUE,
        defvar.row = x), list(exp = expression))) }) 
}
evalWrapper(A + B + C, model, 1:N)

Thanks for the feedback!

Your request number 2 can be done with an mxRowObjective. Examples and details are at ?mxRowObjective, but it's essentially a map-reduce algebra. You specify an algebraic calculation to be performed at each row that must evaluate to a row matrix (so, the algebra might return a 1x2 matrix). Those results are aggregated into rows of an output matrix (in this case, Nx2), and a second algebra is performed on that matrix (easiest would be just a total sum).

Number 1 can be done either with a wrapper function (see Michael's answer) or as the first part of an mxRowObjective, as above.

User-specified gradients/hessians are on the to-do list, but had dropped lower on the list because (I think) the perception was that user interest was pretty low. As you mentioned, some of the scaffolding for it is already there, but there are some details (for example, the user-side interface) that still need to be worked out. But thanks for the request -- we'll bump the feature a bit higher up on the feature request list.