Claude Code is effective as a single agent, but running it once for one task is a limited use of the capability. Many teams want to run multiple Claude Code instances in parallel — different agents on different issues, different repos, or different roles in a review chain.
The tools in this category help you manage multiple concurrent Claude Code sessions without collision, with varying levels of governance and automation.
Self-hosted orchestration layer built specifically for running teams of Claude Code agents. Assigns roles (developer, tech lead, QA, release manager), uses a fabric event bus to hand work between agents automatically based on GitHub label changes, enforces per-agent budgets, and maintains a full decision audit trail. 120+ prompt templates. Single Go binary, no Docker — it runs on your own infrastructure and your source code stays private. Free tier for one slot, $49/slot/month for teams.
Best for: Teams that want to run a fully autonomous software delivery team with governance, budgets, and audit trails on self-hosted infrastructure.
Open-source tool for running multiple Claude Code instances in parallel tmux sessions. Lightweight, easy to set up, and provides a terminal UI for switching between sessions. No governance layer.
Best for: Developers who want to run several parallel Claude Code sessions with minimal setup and no infrastructure overhead.
Mac app from Melty Labs (a third party, not Anthropic) for managing multiple Claude Code and Codex agents. Each agent runs in its own isolated git worktree, with a unified dashboard to spin up and monitor parallel agents.
Best for: Mac users who want a desktop UI for parallel Claude Code management with minimal configuration.
Desktop GUI app (Electron) for running multiple Claude Code and Codex sessions in parallel git worktrees, with built-in branch isolation, session persistence, and rebase/squash helpers. Focused on the developer experience of juggling multiple agents.
Best for: Developers who want a polished desktop UX for managing multiple parallel agent sessions.
Python framework that can orchestrate multiple Claude Code or other agents with defined roles and task routing. Requires writing Python configuration code.
Best for: Teams that want to build custom multi-agent Claude Code workflows with full code control.
Graph-based orchestration framework that can coordinate multiple agents including Claude Code. Highly flexible state machine model for complex workflows.
Best for: Engineers who need a programmable coordination layer and are comfortable with a graph-based workflow model.
Fleet is the purpose-built answer for running multiple Claude Code agents as an autonomous team. It handles not just parallel execution (which Claude Squad and Conductor also do) but the full coordination lifecycle: work assignment from GitHub issues, role-based handoffs through the delivery chain, per-agent budget enforcement, risk scoring, and audit logs. If you want two Claude Code windows open, use Claude Squad. If you want an autonomous engineering team that handles its own work queue, use Fleet.
Pick Claude Squad or Conductor if you want simple parallel Claude Code session management with no governance overhead.
Pick Fleet if you want autonomous role-based coordination, per-agent budgets, event-driven handoffs, and an audit trail.
Pick CrewAI or LangGraph if you need to build a custom multi-agent pipeline in Python.
Pick Crystal if you want the best desktop GUI for managing multiple parallel sessions.
Yes. Each Claude Code agent makes independent API calls, so parallel agents multiply token consumption. Note that Fleet does not meter or cap token usage or your Anthropic bill. What Fleet does enforce is a per-agent run-time budget — a cumulative run-duration cap measured in seconds — and, separately, a risk model that auto-quarantines an agent when its risk level reaches critical. Those controls bound how long and how autonomously agents run, not how many tokens they consume.
With proper branch management, yes. Fleet assigns each agent to its own branch and uses GitHub labels to coordinate handoffs, preventing multiple agents from modifying the same files simultaneously. Without orchestration, managing branch conflicts across parallel sessions requires manual coordination.
One binary. Five minutes. See every agent, coordinate every handoff, and keep a full audit trail of what your fleet did.
