Random generation of a finite Gaussian Markov Chain

Everything that I want to do is done through this code

sd = 1
v = c(0)

for (i in 1:10) {
  rnorm(1,v[i],sd) -> v[i+1]
}
v

But I want to build confidence on Markov Chains, starting through chain generation. There are many packages in R dealing with discrete Markov Chains generation, but ideally I would like a function like this:

PSEUDOCODE:

rGaussMC(n = 10, start_value = 0, sd = 1)

I am open to suggestions for packages, and I am interested in knowing strengths and cool features of those packages.

I would be interested in one package that collects RNG functions for many processes, not only Gaussian.