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Software is incrementally evolved as various new feature requests are implemented to meet users' requirements. To accelerate the incoming feature implementation, developers often utilize existing third-party APIs that encapsulate featurerelated functionality into simple APIs. However, it is non-trivial for developers to choose which APIs to use and where to use them in a target program since the search space of APIs and their usage locations are usually large. In this paper, we introduce a tool, MULAPI, to facilitate the decision of suitable APIs at potential usage locations for implementing the incoming feature requests. MULAPI combines feature localization and information retrieval techniques to accomplish API recommendation and usage location. Empirical studies demonstrate that MULAPI can effectively recommend correct APIs and their usage locations with higher precision than state-of-the-art approaches. The video of our demo is available at https://youtu.be/s3Cs5ltqdvs. © 2019 IEEE.