Kiro Crew

Kiro Crew is an open-source personal AI agent that runs on your own hardware, locally or on a remote host, and stays running. Kiro’s documentation describes it as persistent, self-learning, and self-evolving, and it is the fifth surface alongside the IDE, CLI, Web, and mobile.

What is Kiro Crew?

The other four surfaces are session-shaped. You open one, do something, and close it. Crew is the opposite: a gateway process that stays up, holds memory, runs scheduled jobs, watches for triggers, and can be reached from a dashboard or from a chat app on your phone.

It was open-sourced on August 4, 2026 under the Apache 2.0 licence and picked up coverage from InfoQ, InfoWorld, Forbes, and DevOps.com. That matters for two reasons: you can read the code, and, because the project is young and moving quickly, you should check its documentation rather than trusting a page like this one for details that change.

How it differs from the other always-on options

Four things in Kiro can run without you sitting there, and they are easy to conflate:

	Runs on	Shape	Reaches	Output
Kiro Crew	Your hardware, local or remote	Persistent process	Dashboard, Slack, Discord, Telegram, Teams, and more	Artifacts, files, messages, whatever the job produces
Web Automations	AWS	Scheduled runs (hourly / daily / CRON)	GitHub, GitLab repositories	A pull request per run
Cloud sessions	AWS	One durable session you attach to	The repository fixed at creation	Session work you review
CLI headless	Wherever you run it	One non-interactive command	Whatever the runner can reach	Whatever your pipeline does with it

The rule of thumb: if the work is repository-shaped and belongs in a PR, that is Kiro Web. If it belongs in your CI pipeline, that is headless CLI. If it is a long task you want to check on from another machine, that is a cloud session. If it is an assistant that should still be there tomorrow, on hardware you control, that is Crew.

How to install it

Four paths, all documented:

• Desktop app. Signed .dmg for macOS, a signed installer for Windows, and .deb, .rpm, and .AppImage for Linux, on x86_64 and ARM64.
• One-liner. curl -fsSL https://download.crew.kiro.dev/cli.sh | sh
• Python package. pip install kirocrew, with extras available as pip install "kirocrew[voice]" and pip install "kirocrew[aws]".
• Docker. ghcr.io/kirodotdev/kirocrew:stable, with insider, nightly, and version tags also published.

Prerequisites. Python 3.10 or newer, 3.12 recommended. Node.js 22 or newer only if you are building the dashboard yourself, which the wheel, desktop, and Docker paths do not require. And kiro-cli for model access, which the desktop app installs on first launch.

The three commands to know:

kirocrew setup     # interactive wizard
kirocrew doctor    # verify the installation
kirocrew gateway   # start the server at http://localhost:5476

Data lives in ~/.kiro/crew/, overridable with KIROCREW_HOME, and the port is 5476, overridable with KIROCREW_PORT.

Running it 24/7

As a service. kirocrew service install registers a systemd unit on Linux or a launchd job on macOS. From there, kirocrew service status, kirocrew restart, and kirocrew logs -f are the operational commands, and kirocrew token --ttl 2h issues a time-limited access token.

In Docker.

docker run -d --name kirocrew \
  -p 127.0.0.1:5476:5476 \
  -v kirocrew-home:/home/kirocrew \
  ghcr.io/kirodotdev/kirocrew:stable

docker exec -it kirocrew kiro-cli login

Note the 127.0.0.1: prefix on the port mapping. That is deliberate.

On a remote host. Supported Linux distributions are Ubuntu 22.04+, Debian 12+, Fedora, and Amazon Linux 2023. Plan for roughly 10 GB of RAM minimum and 16 GB recommended, which puts this above the smallest VPS tiers. The dashboard binds to loopback only by default, so you reach it with a tunnel:

ssh -L 5476:localhost:5476 user@host

Interfaces

Crew is unusual in how many places it can be reached from: the desktop app, the web dashboard at localhost:5476, its own CLI, and a long list of messaging platforms including Slack, Discord, Telegram, Teams, Webex, WeChat and WeCom, WhatsApp (linked by QR code), iMessage through a macOS bridge, and Feishu or Lark. All of them share the same memory, skills, and scheduled jobs, so a conversation started in Slack is the same agent you see in the dashboard.

What it can do

The documented feature set is broad:

• Subagents. Parallel background agents.
• Scheduling. Recurring jobs, reactive monitoring, and external triggers.
• Artifacts. Versioned output with live preview and one-click deploy to your own AWS account.
• Multi-instance. Manage remote Crews over SSH.
• Task Runner. Autonomous execution with planning, validation, retry, and checkpoints.
• Memory. Preferences, history, lessons, and semantic facts.
• Knowledge. A curated documentation library.
• Snapshot and restore. Capture and roll back state.
• Browser. Real browser automation with a live view.
• Computer Use. Desktop control on macOS and Windows, off by default.
• Workflows. Multi-agent fan-out and pipelines defined as Python scripts.

Underneath, the building blocks are the ones you already know. Crew’s agent capabilities page lists Agents, Agent Templates, Integrations (MCP), Skills, Steering, Hooks, and Prompts, which is the same vocabulary as the rest of Kiro.

Apps and the App Store

An app is a package that adds agents, skills, MCP servers, cron jobs, dashboard pages, or backend processes. Crew has a built-in App Store: Install clones the repository and Enable registers it. Federated registries are supported, so an organization can run its own.

Third-party apps are disabled by default, behind a toggle under Settings → Security. Leave that off until you have read what you are enabling. Press coverage at launch named DevFleets (worktree management), Issue Radar (issue and PR triage), and Task Runner as reference apps announced at launch.

The security model

This is the part that deserves the most attention, because an always-on agent on your own machine is a different risk profile from a chat window.

• Owner lock on channels, so a Slack or Telegram connection answers to you rather than to anyone who finds it.
• 137 denied command patterns, covering things like rm -rf /, pushes to protected branches, reading ~/.aws/credentials, and requests to the instance metadata service.
• Governance ceiling: where policies overlap, the tightest one wins.
• Sensitive-path blocking and input validation.
• Tool approval levels: Interactive by default, with Trust this command, Trust this tool, and Autopilot. Deny rules are still enforced under Autopilot.
• OS sandbox with three modes. Auto hides .gnupg, .gcloud, .azure, and .docker. Strict additionally hides .aws, .ssh, and .kube. Off is available on Linux and macOS only.
• Output redaction of more than fifteen credential patterns, plus an encrypted secrets vault.
• A signed audit log, inspected with kirocrew security events, kirocrew security audit, and kirocrew security verify.

What it costs

Crew’s documentation lists no separate price for Crew itself. The software is Apache 2.0 and runs on hardware you already pay for. Its model calls go through kiro-cli, so Kiro credits apply to the work it does, drawn from the same pool as the IDE, CLI, and Web. A scheduled job every fifteen minutes is a standing credit commitment; treat it like one. Credits & Pricing covers the plans and the pool.

Common mistakes

Exposing port 5476. The dashboard binds to loopback for a reason. The fix: SSH tunnel, not a firewall rule.

Enabling third-party apps to see what they do. An app can add agents, MCP servers, cron jobs, and backend processes. The fix: read first, enable one at a time.

Turning on computer use because it sounds impressive. Desktop control is off by default, and an agent that can move your mouse is a much larger blast radius than one that can edit files. The fix: leave it off until a specific job needs it.

Undersizing the host. Below roughly 10 GB of RAM you are fighting the machine. The fix: size for 16 GB if this is going to run permanently.

Assuming this page is current. Crew was open-sourced weeks before this was written and is moving quickly. The fix: check the Crew documentation for anything you are about to depend on.

Where it fits

Crew is the persistent layer beside the four session-shaped surfaces. It shares Kiro’s vocabulary (agents, skills, steering, hooks, MCP) and its model access, but it is hosted by you rather than by AWS, which is the whole point of it. If the appeal is “an agent that is always there and answers in Slack”, that is Crew. If the appeal is “work on my repositories from a browser”, that is Kiro Web.

Learn more

• Run Kiro Crew 24/7 is the service and Docker walkthrough.
• Core Concepts maps the building blocks Crew shares with the rest of Kiro.
• Kiro Web is the hosted alternative for repository work.
• Cloud sessions covers AWS-hosted durable sessions.
• Credits & Pricing explains what Crew’s model calls consume.