Is Loss value (e.g., MSE loss) used in the calculation for parameter update when doing gradient descent?

My question is really simple. I know the theory behind gradient descent and parameter updates, what I really haven't found clarity on is that is the loss value (e.g., MSE value) used, i.e., multiplied at the start when we do the backpropagation for gradient descent (e.g., multiplying MSE loss value with 1 then doing backprop, as at the start of backprop we start with the value 1, i.e., derivative of x w.r.t x is 1)?

If loss value isn't used what is the point of it except for evaluating if our network has been trained properly or not??