Analysis within the field of Multidisciplinary Design Optimization (MDO) generally falls under the headings of architecture proofs and sensitivity information manipulation. We propose a differential geometry (DG) framework for further analyzing MDO systems, and here, we outline the theory undergirding that framework: general DG, Riemannian geometry for use in MDO, and the translation of MDO into the language of DG. Calculating the necessary quantities requires only basic sensitivity information (typically from the state equations) and the use of the implicit function theorem. The presence of extra or non-differentiable constraints may limit the use of the framework, however. Ultimately, the language and concepts of DG give us new tools for understanding, evaluating, and developing MDO methods; in Part I, we discuss the use of these tools and in Part II, we provide a specific application.