Currently a large percentage of Internet traffic consists of music files, typically stored in MP3 compressed audio format, shared and exchanged over Peer-to-Peer (P2P) networks. Searching for music is performed by specifying keywords and naive string matching techniques. In the past years the emerging research area of Music Information Retrieval (MIR) has produced a variety of new ways of looking at the problem of music search. Such MIR techniques can significantly enhance the ways user search for music over P2P networks. In order for that to happen there are two main challenges that need to be addressed: 1) scalability to large collections and number of peers, 2) richer set of search semantics that can support MIR especially when retrieval is content-based. In this paper, we describe a scalable P2P system that uses Rendezvous Points (RPs) for music metadata registration and query resolution, that supports attributevalue search semantics as well as content-based retrieval. The perf...