Simple answer is, it might not be possible to do it.
The large number of contigs suggests to me that a short-read sequencing method (such as Illumina sequencing) was used. Alone, short-read sequencing technologies cannot resolve repetitive sequences that are longer than the length of the reads. This is why you have a large number of contigs.*
*You might already have done this, but if you did not, it might be worth checking that your MAG is not actually a mixture of different genomes. This can also somewhat increase the contig number and, more importantly, can skew your interpretation if you assume it's only one organism. There are various ways to test this, but the simplest I know is the program CheckM. To run it you will need a way to use Unix/Linux (could be on a virtual machine). If you are not familiar with Unix, bash and conda, I would heartily suggest software carpentry lessons such as The Unix Shell (https://swcarpentry.github.io/shell-novice/) and possibly this conda lesson although it is in beta and I haven't tested it https://carpentries-incubator.github.io/introduction-to-conda-for-data-scientists/
I'm not familiar with the term 'molecular typing', but it looks like you're interested in what organisms / genes there are in your sample? You probably might not need a full genome for that.
Small probability of helping - but it might also be good to have a look at the sizes of your contigs. You might luck out and have a few large contigs (hundred thousand - million basepairs) which could be compared to existing database genomes.