Label-free proteomics with trace clinical samples provides a wealth of actionable insights for personalized medicine. Clinically acquired primary cells, such as circulating tumor cells (CTCs), are usually with low abundance that is prohibitive for conventional label-free proteomics analysis. Here, we present a sickle-like inertial microfluidic system for online rare cell separation and tandem label-free proteomics (namely, Orcs-proteomics). Orcs-proteomics adopts a buffer system with 0.1% N-dodecyl β-d-maltoside (DDM), 1 mM Tris (2-carboxyethyl) phosphine (TCEP), and 2 mM 2-chloroacetamide (CAA) for cell lysis and reductive alkylation. We demonstrate the application of Orcs-proteomics with 293T cells and manage to identify 913, 1563, 2271, and 2770 protein groups with 4, 13, 68, and 119 cells, respectively. We then spike MCF7 cells with white blood cells (WBCs) to simulate the patient's blood sample. Orcs-proteomics identifies more than 2000 protein groups with an average of 61 MCF7 cells. We further recruit two advanced breast cancer patients and collect 5 and 7 CTCs from each patient through minimally invasive blood drawing. Orcs-proteomics manages to identify 973 and 1135 protein groups for each patient. Therefore, Orcs-proteomics empowers rare cells simultaneously to be separated and counted for proteomics and provides technical support for personalized treatment decision making with rare primary patient samples.