Introducing Klavis Sandbox-as-a-Service: Deterministic MCP Environments for AI Agent Training and Evaluation

Klavis Sandbox-as-a-Service provides deterministic, isolated environments for training and evaluating AI agents. It addresses the risks of testing against live production APIs by offering ephemeral, stateful instances of real SaaS tools like Salesforce or Google Calendar. Developers can initialize these sandboxes with custom data, allow an agent to interact with them via the Model Context Protocol (MCP), and then programmatically verify the final state or reset the environment. This infrastructure enables reliable functional benchmarking for agent performance and creates stable reinforcement learning (RL) training loops for complex tasks.