I would strongly advise you to mock the server. Servers go down, the behavior changes, and if a test failure implies "maybe my code still works", you have a problem on your hands, because your test doesn't tell you whether or not the code is broken, which is the whole point.
As for how to mock the server, for a unit test that does this:
first_results = list_things()
delete_first_thing()
results_after_delete = list_thing()
I have a mock data structure that looks like this:
{ list_things_request : [first_results, results_after_delete],
delete_thing_request: [delete_thing_response] }
It's keyed on your request, and the value is an array of responses for that request in the order that they were seen. Thus you can support repeatedly running the same request (like listing the things) and getting a different result. I use this format because in my situation it is possible for my API calls to run in a slightly different order than it did last time. If your tests are simpler, you might be able to get away with a simple list of request/response pairs.
I have a flag in my unit tests that indicate if I am in "record" mode (that is, talking to a real server and recording this data-structure to disk) or if I am in "playback" mode (talking to the datastructure). When I need to work with a test, I "record" the interactions with the server and then play them back.
I use the little-known SenTestCaseDidStartNotification to track which unit test is running and isolate my data files appropriately.
The other thing to keep in mind is that instability is the root of all evil. If you have code that does things with sets, or gets the current date, and such, this tends to change the requests and responses, which do not work in an offline scenario. So be careful with those.