The major histocompatibility complex (MHC) plays a central role in the vertebrate adaptive immune system and has been of long-term interest in evolutionary biology. While several protocols have been developed for MHC genotyping, there is a lack of transparent and standardized tools for downstream analysis of MHC data. Here, we present the r package mhctools and demonstrate the use of its functions to (i) assist accurate MHC genotyping from high-throughput amplicon-sequencing data, (ii) infer functional MHC supertypes using bootstrapped clustering analysis, (iii) identify segregating MHC haplotypes from family data, and (iv) analyse functional and genetic distances between MHC sequences. We employed mhctools to analyse MHC class I (MHC-I) amplicon data of 559 great reed warblers (Acrocephalus arundinaceus). We identified 390 MHC-I alleles which clustered into 14 functional supertypes. A phylogenetic analysis and analyses of positive selection suggested that the MHC-I alleles belong to several distinct functional groups. We furthermore identified 107 segregating haplotypes among 116 families, and found substantial variation in diversity with 4-21 MHC-I alleles and 3-13 MHC-I supertypes per haplotype. Finally, we show that the great reed warbler haplotypes harboured combinations of MHC-I supertypes with greater functional divergence than observed in simulated populations of possible haplotypes, a result that is in accordance with the divergent allele advantage hypothesis. Our study demonstrates the power of mhctools to support genotyping and analysis of MHC in non-model species, which we hope will encourage broad implementation among researchers in MHC genetics and evolution.