Viral fusion proteins are essential to allow enveloped viruses (such as Influenza, Dengue, HIV and SARS-CoV-2) to enter their hosts’ cells, in a mechanism referred to as membrane fusion. This makes these proteins (with special relevance to their fusion peptides, the com ponent of the protein that can insert into the host’s membrane by itself) interesting potential therapeutic targets for preventing or treating for some well-known diseases. However, there is no centralized data repository containing all the relevant information regarding viral fusion proteins. With that in mind, the main purpose of this work is to develop a CRUD (Create, Read, Update and Delete) web server that will allow researchers to find all the necessary data regarding viral fusion proteins, through an easy-to-use web interface. The web application will also contain other bioinformatics functionalities, such as sequence alignment (through BLAST, Clustal and Weblogo) to allow researchers to retrieve key pieces of information regarding a fusion protein, as well as machine learning models capable of predicting the location of fusion peptides inside the viral fusion protein sequence. The implementation of the server used Django as its back-end, retrieving the data from a MySQL database, and Angular as its front-end. The main result of the work is, therefore, a working webserver, with a web interface available online through the URL: https://viralfp.bio.di.uminho.pt/. The web application allows users to explore the gathered data related to viral fusion proteins in a user-friendly way. This tool contains all the proposed functionalities and machine learning models. As expected in an application’s development, there are several aspects that require future work to improve the usefulness of this tool to the scientific community.