3D Gaussian Splatting (3DGS) has revolutionized real-time rendering with state-of-the-art novel view synthesis, but its applicability to accurate geometric measurement remains limited. Compared with multi-view stereo (MVS)-based point clouds or mesh models, 3DGS provides superior visual quality and completeness, while existing measurement approaches still rely on stereoscopic workstations or direct measurements on incomplete and inaccurate reconstructed geometry. As a novel view synthesizer, 3DGS reproduces source views and smoothly interpolates intermediate viewpoints, enabling users to intuitively identify congruent points across multiple views. By triangulating these correspondences, accurate 3D point measurements can be obtained. Inspired by traditional stereoscopic measurement, the proposed approach removes the need for stereo workstations and biological stereoscopic capability, while naturally supporting multi-view measurements for improved accuracy. We implement a web-based application to demonstrate this proof of concept using UAV-based aerial datasets. Experimental results show that the proposed method achieves measurement accuracy comparable to or better than traditional stereoscopic measurement approaches while operating entirely on non-stereo workstations. In particular, the proposed method consistently outperforms direct mesh-based measurements, achieving RMSEs of 1–2 cm on well-defined points. On challenging thin structures, the proposed method reduces RMSE from 0.062 m to 0.037 m, and successfully measures sharp corners where mesh-based methods fail entirely. The source code and documentation are open-source and available at: <code>https://github.com/GDAOSU/3dgs_measurement_tool</code>.