The increasing complexity of modern embedded streaming applications imposes new challenges on system designers nowadays. For instance, the applications evolved to the point that in many cases hard-real-time execution on multiprocessor platforms is needed in order to meet the applications' timing requirements. Moreover, in some cases, there is a need to run a set of such applications simultaneously on the same platform with support for accepting new incoming applications at run-time. Dealing with all these new challenges increases significantly the complexity of system design. However, the design time must remain acceptable. This requires the development of novel systematic and automated design methodologies driven by the aforementioned challenges. In this paper, we propose such a novel methodology for automated design of an embedded multiprocessor system, which can run multiple hard-real-time streaming applications simultaneously. Our methodology does not need the complex and time-consuming design space exploration phase, present in most of the current state-of-the art multiprocessor design frameworks. In contrast, our methodology applies very fast yet accurate schedulability analysis to determine the minimum number of processors, needed to schedule the applications, and the mapping of applications' tasks to processors. Furthermore, our methodology enables the use of hard-real-time multiprocessor scheduling theory to schedule the applications in a way that temporal isolation and a given throughput of each application are guaranteed. We evaluate an implementation of our methodology using a set of real-life streaming applications and demonstrate that it can greatly reduce the design time and effort while generating high quality hard-real-time systems.