Developer preferences, language capabilities and the persistence of older languages contribute to the trend that large software codebases are often multilingual -that is, written in more than one computer language. While developers can leverage monolingual software development tools to build software components, companies are faced with the problem of managing the resultant large, multilingual codebases to address issues with security, efficiency, and quality metrics. The key challenge is to address the opaque nature of the language interoperability interface: one language calling procedures in a second (which may call a third, or even back to the first), resulting in a potentially tangled, inefficient and insecure codebase. An architecture is proposed for lightweight static analysis of large multilingual codebases -the MLSA architecture. Its modular and table-oriented structure addresses the open-ended nature of multiple languages and language interoperability APIs. We focus here as an application on the construction of call-graphs that capture both inter-language and intra-language calls. The algorithms for extracting multilingual call-graphs from codebases are presented, and several examples of multilingual software engineering analysis are discussed. The state of the implementation and testing of MLSA is presented, and the implications for future work are discussed.1. The procedure-based interoperability API call is tested for in line 3 (e.g., PyObject_CallObject) 2. The name of the procedure, if it is statically available, is added to the modified call-graph CGM at lines 8 and 11, and the arguments to the procedure are modified to omit the first argument. 3. The node is labelled "ProcBased-Dynamic" at line 6 This algorithm does not include several steps typically associated with procedure-based interoperability calls. Continuing our python.h example: