dSPACE, a provider of simulation and validation technologies, is introducing Model Context Protocol-enabled workflows that connect AI agents directly with its automotive engineering tools. Built around the open Model Context Protocol, the approach is designed to move engineering teams beyond isolated, prompt-based tasks by allowing AI agents to assist with connected workflows extending from requirements and specifications through simulation and validation on real-time hardware.

Automotive development programs frequently manage requirements, system specifications, simulations, software implementations and test results in separate engineering environments. MCP gives AI agents standardized interfaces for interacting with compatible tools, reducing the manual handoffs required as work moves between development stages. Engineers remain responsible for reviewing and approving activities and results, preserving human oversight throughout the process.

Electronics Industry Monthly graphic of a person using a touchscreen interface to represent dSPACE MCP-enabled automotive simulation and validation workflows.

dSPACE is introducing MCP-enabled AI workflows that connect AI Agents directly with dSPACE tools.

Within the dSPACE environment, AI agents can assist with interpreting requirements, refining specifications, developing software and preparing simulations. They can also orchestrate validation across VEOS, ConfigurationDesk, SystemDesk, Bus Manager and ControlDesk, together with dSPACE real-time hardware. Results gathered during testing can then be returned to the development workflow, helping engineers refine specifications and implementations as they evaluate system performance.

“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,” said 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.”

Connecting AI agents with simulation, configuration, measurement and validation tools can reduce repetitive setup work while preserving links between engineering requirements, implementations and test results. Instead of treating each interaction with an AI agent as a separate task, development teams can use MCP to support a broader specification-driven process in which validation findings contribute to continued refinement. This approach is particularly relevant to automotive programs that must evaluate software in virtual environments before progressing to validation on real-time hardware.

About dSPACE

Founded in 1988 as a spin-off from the University of Paderborn, dSPACE develops simulation and validation technologies for embedded and mechatronic system development. The independent, family-owned company provides software and hardware for rapid control prototyping, production software development, software-in-the-loop testing, hardware-in-the-loop testing, data-driven development and system validation. Headquartered in Paderborn, Germany, dSPACE supports customers through engineering and operating locations across Europe, the Americas and Asia. For more information, please click here.

Source/Photo Credit: dSPACE

(Editor’s Note: All trademarks mentioned in this article, including company names, product names, and logos, are the property of their respective owners. Use of these trademarks is for informational purposes only and does not imply any endorsement.)

Molly Bakewell Chamberlin
Latest posts by Molly Bakewell Chamberlin (see all)
Tagged