Guides·Guide

How to run multiple OpenClaw agents

From two agents on a laptop to a fleet in production: how multi-agent OpenClaw actually works, and where it breaks.

TL;DR

OpenClaw runs multiple agents natively: each agent is isolated, with its own identity, workspace and state, and you route channels to the right agent with bindings. Doing it on one machine is easy; keeping many alive in production is a different job.

  • One gateway can host several isolated agents, each with its own personality, skills, model and memory.
  • Channel bindings route a chat, an inbox or a number to a specific agent.
  • On a single box this is a config exercise. Across many agents 24/7 it becomes infrastructure: crashes, memory spikes and version updates multiply per agent.

What "multiple agents" means in OpenClaw

OpenClaw supports multiple agents on the same gateway out of the box. Each agent is isolated: its own identity, its own workspace and files, its own skills and model routing, and its own memory and state. They do not share context unless you wire them to.

You decide which incoming channel reaches which agent with bindings: a chat, a phone number, an email inbox or a webhook is bound to a specific agent, so one OpenClaw install can run a dev agent, a support agent and a marketing agent side by side without them stepping on each other.

  • Isolated agents: separate identity, workspace, skills, model and memory per agent.
  • Bindings: deterministic routing from a channel or account to one agent.
  • Per-agent state: each keeps its own history and files between tasks.

Running a few agents on one machine

On a single machine the setup is straightforward. You run one gateway, add each agent with its own configuration, give each one an identity and the skills it needs, then bind the channels that should reach it. For a personal stack or a handful of roles this is enough, and it is free beyond your own compute and the model provider you use.

The OpenClaw documentation and community setups (one-command multi-agent installs, group routing, safe config merges) cover this path well. It is the right call when the agents live on hardware you watch yourself.

Where multi-agent setups start to break

The cracks show the moment these agents need to stay up without you watching.

  • Shared memory: agents run on the same machine, so one agent spiking in RAM can starve or crash the others on the node.
  • Silent death: a long-running agent crashes and simply stays down until a human notices, which on a single box means you.
  • Config drift: merging configs for many agents corrupts setups, and one bad config can brick an instance.
  • Version updates: an OpenClaw update that fixes one agent can break another, and you absorb that across every agent on every release.
  • No isolation between owners: a single shared install is fine for your own agents, not for agents that belong to different clients.

One agent

online

Easy to babysit.

A fleet, by hand

onlinecrashedout of memoryconfig broken
Every red, amber or grey square is a silent outage: an agent down until someone notices. One is manageable. Hundreds, each failing in its own way around the clock, is impossible without watchers and automatic recovery.

Multiple agents is not the same as multi-tenant

Running several agents for yourself is a multi-agent setup. Running agents that belong to different customers, each isolated, billed and observed on its own, is multi-tenancy, and that is a harder problem with its own failure modes.

If your goal is to give every client or every employee their own agent, you are no longer doing a config exercise; you are operating a platform. That distinction decides whether you self-host or run on managed infrastructure.

Running many agents at scale, without operating a platform

Once you need many OpenClaw agents online around the clock, recovering on their own, isolated and versioned, you are running infrastructure whether you meant to or not. A managed OpenClaw runtime takes that layer off your plate: it keeps each agent alive with self-healing recovery, packs many safely on shared capacity with over-provisioning instead of one machine per agent, versions each agent's filesystem, and ships 1,000+ integrations, browser automation and email and voice out of the box.

Molted is one such managed operating environment for OpenClaw. The same team runs molted.cloud, where this approach keeps 11,000+ instances alive for 300+ clients, so you run agents instead of babysitting a fleet of them.

FAQ

Q.01

Can OpenClaw run multiple agents at once?

Yes. OpenClaw supports multiple isolated agents on one gateway, each with its own identity, workspace, skills, model and memory. You route channels to the right agent with bindings, so a single install can run several agents in parallel.

Q.02

How many OpenClaw agents can I run on one machine?

As many as the machine's memory allows, which is the real limit. Each agent is a long-running process, and OpenClaw agents can spike in RAM, so on a shared box one agent can crash the others. A handful is fine; a fleet needs memory protection and recovery you either build or get from a managed host.

Q.03

What is the difference between multi-agent and multi-tenant OpenClaw?

Multi-agent means several agents on one install, usually all yours. Multi-tenant means agents that belong to different customers, each isolated, billed and monitored separately. Multi-agent is configuration; multi-tenant is infrastructure. See the multi-tenant OpenClaw guide for the harder case.

Q.04

How do I keep multiple OpenClaw agents alive 24/7?

On your own machine you script restarts, watch memory, repair configs and absorb version updates by hand, per agent. A managed OpenClaw runtime does it for you with automatic crash recovery, safe density across shared capacity and versioned state, so a dead agent comes back before anyone notices.

Going from a few agents to a fleet? See how managed hosting runs many OpenClaw agents at scale, self-healing and isolated.