Aegis Software has introduced built-in Model Context Protocol (MCP) support in Simio, creating a standardized interface between compatible generative AI applications and the company’s discrete-event simulation and advanced planning and scheduling software. The new capability allows users to work with simulation models and production plans through natural language, including generating or refining model logic, investigating how an existing model is structured, troubleshooting errors, running and analyzing experiments, and examining planning results before operational decisions are put into practice.

The distinction between generative AI and the simulation model itself is important. A large language model can interpret a question and generate useful language or logic, but it does not inherently understand the resources, process dependencies, operating constraints and variability within a specific factory, warehouse, hospital or other complex operation. Simio models those relationships through discrete-event simulation and digital twin technology. The new MCP connection gives compatible AI applications a standardized path into that structured operational environment, allowing natural-language interaction with a model that already represents how resources, processes and constraints behave together.

“AI is not new to Simio. Simio has been bringing AI and simulation together for years. What the new built-in MCP support changes is how teams can work with Simio. AI-powered interaction can enable more people to contribute, help experienced users work faster and allow organizations to gain value from simulation and planning sooner,” said Jason Spera, CEO of Aegis Software.

Aegis Software graphic representing generative AI interaction with Simio simulation and production planning software, Industrial Automation Monthly.

Aegis Software’s built-in MCP support connects compatible generative AI applications with Simio simulation, model logic, experiments and production planning, creating a natural-language interface for exploring operational decisions before execution.

Simio already incorporates AI capabilities within its simulation engine, including embedded neural networks that can learn from synthetic data generated during simulation runs and apply that learning to decisions within the model. The platform can generate training data, train neural networks and use trained models for inference as a simulation executes. Built-in MCP support adds a different layer of AI functionality, connecting external large language model applications to Simio so users can interact with the model, its logic and its results conversationally rather than replacing the simulation and optimization capabilities already operating underneath.

That interaction can be particularly useful in complex production models where understanding another engineer’s work may require tracing process logic, resources, constraints and model conventions before meaningful changes can be made. Through the MCP connection, a compatible AI application can help explain how model elements relate to one another, investigate errors and assist with common modeling tasks. In advanced planning and scheduling applications, users can also interrogate production plans and results, including identifying late orders and examining characteristics those orders may share. The simulation remains responsible for representing the operating environment and evaluating scenarios, while generative AI provides another way to access, interpret and work with that information.

“AI-powered interaction can help people become productive with simulation sooner,” said Gregory Lang, Senior Director of Engineering and DevOps, Aegis Software. “Picture joining a team that has already built a simulation model of its operation. Understanding what someone else built takes time. With a compatible AI application connected through Simio’s built-in MCP support, you can quickly see how the model is structured, have its logic explained and ask questions about its behavior. Experienced users can use the same connection to troubleshoot issues and complete common tasks more efficiently.”

The implementation is deliberately model-agnostic rather than tied to a single generative AI provider. Simio supports connection options including Claude Code, Codex, GitHub Copilot CLI and OpenCode, along with other compatible applications using MCP. Organizations can also provide model-specific instructions covering naming conventions, terminology, color rules and other preferences, giving the connected AI additional context about how a particular simulation has been constructed. MCP itself is an open standard for connecting AI applications with external tools and data, allowing Simio to expose defined capabilities without requiring every AI integration to be built separately.

For manufacturing teams, that open approach is significant because simulation and planning environments frequently outlive individual software tools, AI models and user interfaces. Giving organizations the ability to choose compatible AI applications while maintaining the simulation model as the operational reference point can provide greater flexibility as generative AI technology continues to evolve. It also keeps the role of the language model distinct from the role of the digital twin: the AI can help users interrogate, explain and work with the model, while the simulation engine continues to evaluate process behavior, constraints, variability and what-if scenarios.

The capability is also a natural extension of Aegis Software’s broader manufacturing software strategy following its acquisition of Simio in January 2026. That combination brought manufacturing execution together with digital twin simulation and advanced planning and scheduling, creating a software environment that spans production execution, scenario analysis and forward-looking operational planning. Adding an MCP interface introduces another access layer across those simulation and planning workflows, particularly where manufacturers want to understand potential outcomes before making changes on the production floor.

Built-in MCP support is available beginning with Simio Release 20.294. For industrial automation users, the more important development is not simply that generative AI has been added to another software platform. It is the connection of a natural-language interface to a structured simulation environment capable of representing how an operation actually behaves. That combination gives engineers and planners a new way to explore complex models and production decisions while preserving the simulation, constraints and operational logic needed to test those decisions before execution.

About Aegis Software

Founded in 1996 and headquartered in Horsham, Pennsylvania, Aegis Software develops manufacturing execution and operations software for discrete manufacturing environments. Its technology supports production, quality, materials management, analytics and operational visibility across individual lines, factories and multi-site manufacturing organizations. Aegis Software completed its acquisition of Simio in January 2026, adding digital twin simulation, scenario modeling and advanced planning and scheduling capabilities to its manufacturing software portfolio. The company supports more than 2,200 factories across North America, Europe, Asia and Latin America, including manufacturing operations in aerospace, defense, electronics, medical and automotive industries. For more information on Aegis Software and its manufacturing technologies, please click here.

Source/Photo Credit: Aegis Software

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Molly Bakewell Chamberlin
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