Abstract This chapter presents a unifying methodology for developing environmental information systems with software agents. Based on the experience reported in recent literature, we abstract common requirements of environmental information systems into agent types, combine state-of-the-art tools from computer science, service-oriented software engineering and artificial intelligence domains, as software agents and machine learning, and illustrate their potential for solving real-world problems. Specifically, two generic agent types are specified that behave as information carriers and decision makers, which provide an appropriate abstraction for deployment with added-value services in environmental management information systems. A concrete pathway for applying these instruments throughout the software lifecycle of an environmental management information system is outlined, along with suggestions for software specification and deployment. The method is demonstrated in two application domains: one for air quality assessment and another for meteorological radar data surveillance.