Too long for a comment:
Is it possible to use this information to get more information about this asteroid, like its name, orbital details etc?
I don't think it's so simple! When we see a spot in an image at a certain time, yes one can calculate the apparent positions of all known asteroid orbits (almost a million of them!) and see which ones match most closely, then use the apparent magnitude as a secondary matching criteria.
But both of these will have uncertainties; for many objects in the MPC database there may only be a few observations and so their propagated orbits will have positional uncertainties at a given time, and if the object is not a uniform sphere and/or it changes temperature and albedo when it gets closer/further from the Sun, its apparent magnitude will vary.
So I think the best you can get is a list of possible matches, with uncertainties. After that, one should go back a few times hours, days, or months later (depending on its proper motion) and get new positions and see if its movement matches the predicted movement of any of the candidates.
But I am guessing that you know this already, and are asking HOW to do this process in an automated way - from all the data available in MPC.
If you would like a DIY solution, then try the Python package Skyfield. See for example Skyfield: Kepler orbits You could go through all the orbital element sets available at MPC one at a time, propagate them to the date/time of your image, and build a table of close candidates (you decide how close) and then do the same for your next images taken hours/days/months later and write your own filtering algorithm.
But hopefully there will be other answers posted soon with ready-to-run solutions that don't require you working (and debugging) the problem DIY-style from scratch.