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This paper presents a novel concept for a context-aware framework for mission planning anddecentralized execution that integrates heterogeneous teammates such as autonomous drones, agents, and human responders into a unified, resilient system for dynamic operational scenarios. At the operational level, the system utilizes a Mission Planning function that receives high-level objectives, interprets mission intent, and decomposes complex objectives into a series of clear, actionable Mission-Essential tasks and sub-tasks. The process leverages contextual information from various sources such as sensor feeds, human reports and operational databasesto dynamically assess resource availability and execution timing, while also considering operational constraints, including ethical constraints, and cost considerations. The system orchestratesa two-tier command structure, where the first level ensures that subordinates possess a robust understanding of mission objectives and the autonomy to adapt to changes in its operational environment. The second level comprises of diverse agents with varying levels of autonomy andcapabilities, enabling iterative adaptation and collaboration. Experiments will be conducted in dynamic scenarios, such as deploying diverse drone platforms for Intelligence, Surveillance and Reconnaissance, and Search and Rescue missions to validate the framework’s feasibility. This research aims to develop context-awareness for system adaptation to its operational environment with a safety-monitoring function to enhance the safety, adaptability, and efficiency of coordinated drone-human teams in operational applications.