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Green Infrastructure (GI) connects different types of green features via various scales, thereby supporting urban biodiversity and service provision. This study presents a methodology capable of identifying multiple functions to assess GI in less-developed countries, where such methodologies are lacking. GI was assessed based on a high-resolution land use classification using both landscape metrics and spatial data within an urbanized region of San José, Costa Rica, at different scales (watershed, neighbourhood, object). Results showed highly fragmented green spaces (often <10 ha), typically unable to support high levels of biodiversity, along with a low amount of green space per inhabitant (<7.4 m²) within the watershed. Substantially higher tree cover (x6) and tree density (x5) were found in the greenest neighbourhood in comparison to the least green neighbourhood. Potential areas for new GI in the form of green roofs (4.03 ha), permeable pavement (27.3), and potential retention areas (85.3) were determined. Several green spaces (n = 11) were identified as promising GI sites with the potential to increase provision (18.6 m²/inhabitant). The adopted methodology demonstrates the potential of GI for increasing recreational green space access, runoff reduction, and flood retentions while supporting biodiversity, validating its utility in guiding decision-making and policy generation.