flow-nexus-swarm

Cloud-based AI agent swarms are orchestrated by initializing a swarm topology, spawning agents, and executing event-driven workflows with real-time monitoring. This simplifies complex multi-agent coordination across mesh, hierarchical, ring, and star topologies.

Multi-swarm coordination across topologies is configured by selecting mesh, hierarchical, ring, or star network structures during swarm initialization. This enables scalable AI collaboration and structured agent communication across diverse architectural patterns.

Yes, event-driven workflows support message queues and auto-scaling for AI agents. The orchestration system executes workflows with real-time monitoring, allowing dynamic agent coordination and automated scaling based on operational demands.

Real-time monitoring of AI agent workflows is managed through the orchestration interface after spawning agents. The system provides live visibility into event-driven workflows and message queues to track multi-agent execution and coordination.

Yes, vector-based agent assignment and Claude Flow MCP integration are supported. The orchestration system uses vector assignment to match agents to tasks and integrates with Claude Flow MCP for extended workflow and coordination capabilities.

Use hierarchical topology for structured, tiered AI agent coordination with clear command flows, and mesh topology for decentralized, peer-to-peer swarm collaboration. Topology choice depends on your workflow scaling and communication requirements.