Adoptive T cell therapies based on introduction of new T cell receptors (TCRs) into patient recipient T cells is a promising new treatment for various kinds of cancers. A major challenge, however, is the choice of target antigens. If an engineered TCR can cross-react with self-antigens in healthy tissue, the side-effects can be devastating. We present the first web server for assessing epitope sharing when designing new potential lead targets. We enable the users to find all known proteins containing their peptide of interest. The web server returns not only exact matches, but also approximate ones, allowing a number of mismatches of the users choice. For the identified candidate proteins the expression values in various healthy tissues, representing all vital human organs, are extracted from RNA Sequencing (RNA-Seq) data as well as from some cancer tissues as control. All results are returned to the user sorted by a score, which is calculated using well-established methods and tools for immunological predictions. It depends on the probability that the epitope is created by proteasomal cleavage and its affinities to the transporter associated with antigen processing and the major histocompatibility complex class I alleles. With this framework, we hope to provide a helpful tool to exclude potential cross-reactivity in the early stage of TCR selection for use in design of adoptive T cell immunotherapy.