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This paper introduces YAIFS, an extension of the YAFS simulator that enables interactive control and observation of distributed system simulations via a unified API. The key innovation is the integration of the Model Context Protocol (MCP) to standardize agent-simulation interaction, allowing heterogeneous agents to access state, invoke actions, and coordinate behavior. The authors demonstrate the framework's capabilities with an LLM-based assistant for natural language control and a multi-agent system that dynamically adapts placement decisions, showcasing the potential for AI-driven experimentation in cloud-edge systems.
Forget static simulations – YAIFS lets you build interactive, agent-driven cloud-edge environments controllable via LLMs and multi-agent systems.
Simulation plays a key role in the design and evaluation of distributed systems, yet it is often treated as a static tool with limited interaction capabilities. In this work, we present Yet (not) Another Intelligent Fog Simulator (YAIFS), and evolution of YAFS that redefines simulation as an interactive, service-oriented environment. YAIFS introduce a layered architecture that exposes the simulation through a unified API and service interface, enabling external entities to observe, control, and modify its execution. A central contribution is the integration of the Model Context Protocol (MCP) as a standardized interaction layer between agents and the simulation. Through MCP, heterogeneous agents can access state, invoke actions and coordinate behavior using a common set of tools, decoupling agent experimentation workflows. We illustrate these capabilities through two scenarios: an LLM-based assistant that enable natural language control of simulations, and a multi-agent setting where agents monitor system conditions and adapt placement decisions at runtime. These scenarios demonstrate how MCP structures agent-simulation interaction and enable adaptive behavior under dynamic workloads. The proposed approach transforms simulation into an interactive and programmable environment, opening new directions for AI-driven experimentation in cloud-edge systems. The implementation is publicly available at: http://github.com/acsicuib/YAIFS
