What is Mean Reciprocal Rank (MRR) and when is it used?

Mean Reciprocal Rank measures how high the first relevant document appears in the ranking, computed as the average of 1 divided by the rank of the first relevant result across queries. MRR of 1.0 means the first result is always relevant, while 0.5 means the first relevant result is usually at position 2. MRR is useful when users typically look at only the top result or two, such as in FAQ bots or known-item search. For RAG, recall at k is usually more informative because the system uses multiple retrieved chunks.