Context: Quantum computing (QC) is reshaping multiple disciplines by enabling computational capabilities that surpass those of classical systems. However, realizing QC’s potential requires not only access to quantum hardware but also significant domain expertise. Platforms, libraries, and frameworks that offer Quantum Computing as a Service (QCaaS) aim to overcome these barriers by abstracting quantum-specific complexities and enhancing accessibility for a broader range of users. Motivation: The rapid growth of QCaaS platforms and tools underscores the need for a structured and comprehensive understanding of their design properties, functional capabilities, and practical limitations. Critical aspects such as scalability, usability, and maintainability require systematic investigation to support evidence-based decision-making and to guide the development of more effective and sustainable QCaaS ecosystems. Aim: This paper presents preliminary findings from an ongoing systematic mapping study (SMS) that aims to identify, categorize, and synthesize existing toolchains supporting QCaaS. Nine tools were analyzed, selected through a structured search strategy applied across five major digital libraries. These tools were evaluated based on five key characteristics: source code availability, input type, output type, level of automation, and type of evaluation. Results indicate that most tools are open source, support high-level input formats, produce simulated outputs, employ semi-automated processes, and are evaluated through explicit empirical methods. These findings offer an early yet insightful overview of the QCaaS tooling landscape and establish a foundation for further analysis. The extended version of this study will additionally examine architectural concerns (e.g., core components, design principles) and the key challenges involved in the adoption and integration of QCaaS toolchains.