A useful feature in graph query engines is to clarify "Why certain entities (nodes, attribute values or edges) are missing" in query answers. This task is even more challenging when the relevant data is already missing in the underlying data source. Missing data, on the other hand, can be inferred by enforcing data constraints for graphs. We demonstrate GRIP, a system that exploits data constraints to clarify missing answers for graph queries. (1) Constraint-based ex- planation. Given a desired yet missing entity in the query answer, GRIP ensures to generate finite and minimal sequences of data constraints (an "explanation") that should be consecutively enforced to to ensure its occurrence for the same query. (2) Answering ?why" and "how" questions. Users can query GRIP with both "Why" ("Why" the element is missing) and "How" questions ("How" to refine the graph to include the missing answer). GRIP engine supports run- time generation of explanations by incrementally maintaining a set of bi-directional search trees. (3) Interactive exploration. GRIP provides user-friendly GUI to support interactive ad visual exploration of explanations, including both automated generation and step-by-step inspection of graph manipulations.