dSPACE has introduced MCP-enabled AI workflows that connect AI agents directly with the company’s tools, based on the open Model Context Protocol (MCP). This approach helps engineers transition from isolated prompt-based tasks toward connected, specification-driven validation workflows. MCP reduces the need for manual handoffs by enabling AI agents to interact with dSPACE tools through standardized interfaces while keeping engineers in full control of reviewing and approving all activities and results. The MCP-enabled tools support engineering workflows spanning requirements analysis, software development, simulation preparation and validation across VEOS, ConfigurationDesk, SystemDesk, Bus Manager, ControlDesk and real-time hardware. The platform also feeds validation results back into the development process to support iterative engineering. “AI delivers the greatest value when it can actively support engineering workflows rather than operate outside them,” said Jann-Eve Stavesand, director product portfolio management at dSPACE. “With MCP-enabled dSPACE tools, engineers can connect requirements, specifications, implementation and validation activities through AI-supported workflows while maintaining full transparency, traceability and engineering control.” By connecting AI Agents with simulation, configuration, measurement and validation tools, MCP-enabled workflows help reduce manual setup effort and streamline engineering processes, allowing engineers to transition more quickly from requirements and specifications to software validation on real hardware while maintaining full traceability.