The mu opioid receptor (μOR) is a key target for therapeutic and abused drugs. This study describes a proteomics and computational approach to map the proximal proteome of the activated μOR, revealing subcellular location, trafficking, and functional partners of GPCR activity. The μOR's proximal proteome changes are driven by distinct opioid agonists, with endocytosis and endosomal sorting playing a significant role. Two novel μOR network components, EYA4 and KCTD12, are identified, which are recruited based on receptor-triggered G protein activation and may form a buffering system for G protein activity, modulating cellular GPCR signaling. The computational framework developed in this study enables the systematic characterization of μOR cellular responses based on receptor trafficking and interaction networks, providing insights into the molecular mechanisms underlying the different cellular responses evoked by chemically distinct ligands.The mu opioid receptor (μOR) is a key target for therapeutic and abused drugs. This study describes a proteomics and computational approach to map the proximal proteome of the activated μOR, revealing subcellular location, trafficking, and functional partners of GPCR activity. The μOR's proximal proteome changes are driven by distinct opioid agonists, with endocytosis and endosomal sorting playing a significant role. Two novel μOR network components, EYA4 and KCTD12, are identified, which are recruited based on receptor-triggered G protein activation and may form a buffering system for G protein activity, modulating cellular GPCR signaling. The computational framework developed in this study enables the systematic characterization of μOR cellular responses based on receptor trafficking and interaction networks, providing insights into the molecular mechanisms underlying the different cellular responses evoked by chemically distinct ligands.