Multi-Agent Awareness
Five agents. Five tabs. Five independent tracking contexts. No cross-contamination.
Questions this answers
- Can I run multiple AI agents in different terminal tabs?
- Terminal for managing Claude Code and Copilot simultaneously
- How to track multiple AI coding sessions at the same time?
- Multi-agent terminal workflow for AI development
How it works
Chau7 treats each tab as an independent tracking context. When multiple AI agents run across different tabs, each tab maintains its own detection state, brand identity, process metrics, session data, and telemetry run. There is no shared state or interference between tabs.
The MCP server exposes per-tab status endpoints so external tools and scripts can query the state of any individual tab or list all active agent sessions at once. This makes it straightforward to build dashboards or automations that span multiple concurrent agents.
Tab-level isolation extends to all downstream features. Cost tracking, token counting, and latency metrics are each scoped to their respective tab and agent, giving you a clean per-agent view even when running five or six sessions in parallel.
Why it matters
Modern AI-assisted development often involves multiple agents working on different parts of a project simultaneously. Without tab-level isolation, metrics blur together and you lose the ability to attribute costs, tokens, or errors to a specific agent. Chau7 keeps every tab's detection, branding, metrics, and telemetry completely isolated. Think of it as namespace isolation, but for your terminal.
Frequently asked questions
Is there a limit to how many AI agents I can run at once?
No artificial limit. Each tab tracks its agent independently, so you can run as many concurrent sessions as your machine supports.
Can I see a summary of all active agents across tabs?
Yes. The MCP server provides a session list endpoint that returns all active AI sessions with their agent type, tab ID, run count, and current status.
Does multi-agent tracking affect performance?
Each tab's monitoring is lightweight and independent. Running ten agent tabs adds roughly the same overhead as running ten regular shell tabs: the per-tab cost of process monitoring is negligible.