dSPACE Connects AI Agents to Automotive Validation Workflows with MCP

MCP-enabled tools support spec-driven workflows from requirements to simulation, hardware execution, and continuous refinement

Paderborn, Germany, 31.7.2026 – dSPACE is introducing MCP-enabled AI workflows that connect AI Agents directly with dSPACE 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.

In modern automotive development, requirements, specifications, simulations, implementations, and tests are often managed in different tools and environments. 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.

MCP-enabled dSPACE tools allow AI Agents to support end-to-end engineering workflows. These workflows include interpreting requirements, refining specifications, assisting with software development, preparing simulations, and orchestrating validation across VEOS, ConfigurationDesk, SystemDesk, Bus Manager and ControlDesk, and real-time hardware. They also include feeding the resulting insights back into the development process.

“AI delivers the greatest value when it can actively support engineering workflows rather than operate outside them. 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,” says Jann-Eve Stavesand, Director Product Portfolio Management at dSPACE. “This allows engineering teams to streamline their validation workflows and transition more efficiently from requirements to verified implementations.”

By connecting AI Agents with simulation, configuration, measurement, and validation tools, MCP-enabled workflows help reduce manual setup effort and streamline engineering processes. Engineers can transition more quickly from requirements and specifications to software validation on real hardware, while maintaining full traceability throughout the process. Validation results can be fed back directly into development workflows, enabling continuous refinement and accelerating the path from concept to validated implementation.