> For the complete documentation index, see [llms.txt](https://omniminds-ai.gitbook.io/whitepaper/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://omniminds-ai.gitbook.io/whitepaper/9.-use-cases-and-applications/ai-to-ai-coordination-multi-agent-workflows.md).

# AI-to-AI Coordination (Multi-Agent Workflows)

As AI agents become more prevalent, there's a need for interoperability — agents that can delegate, coordinate, or extend each other's tasks. Omniminds’ LaunchBay enables multi-agent triggering via the Multi-Agent Coordination Protocol (MCP). Agents can call each other based on output conditions, time triggers, or task handoffs. For example, a voice AI schedules meetings → triggers a LaunchBay agent to open calendars and book time slots → notifies a separate notification agent.