Maux is a SaaS AI agent platform that lets teams design, configure, and launch intelligent autonomous agents without deep infrastructure management. Users can choose from modular templates, customize prompt chains, and integrate with APIs like Slack, CRM systems, or databases. Maux supports multi-agent orchestration, letting agents communicate and coordinate on complex tasks. Built-in monitoring dashboards and logs provide insight into performance, usage metrics, and error handling. The platform also offers version control, role-based access, and webhook triggers, enabling seamless deployment of production-grade AI agents for customer support, research automation, data processing, and workflow automation.

Java-Action-Storage is a core component of the LightJason multi-agent framework designed to handle the end-to-end persistence of agent actions. It defines a generic ActionStorage interface with adapters for popular databases and file systems, supports asynchronous and batched writes, and manages concurrent access from multiple agents. Users can configure storage strategies, query historical action logs, and replay sequences to audit system behavior or recover agent states after failures. The module integrates via simple dependency injection, enabling rapid Adoption in Java-based AI projects.

MCP Agent Proxy acts as a middleware service between your applications and the OpenAI API. It transparently forwards ChatCompletion and Embedding calls, handles streaming responses to clients, caches results to improve performance and reduce costs, logs request and response metadata for debugging, and allows on-the-fly customization of API parameters. Developers can integrate it into existing agent frameworks to simplify multi-channel processing and maintain a single managed endpoint for all AI interactions.