Kiro Crew

A persistent workspace for development work that self-improves and continues beyond one session.

Kiro Crew is an open source development workspace that runs locally or remotely on your hardware. It is persistent, self-learning, and self-evolving. Work with it from the desktop app, web dashboard, and CLI, or continue the same work through connection tools like Slack and Discord. Your multi-step tasks can run unattended, recurring jobs run on your schedule, and heartbeats monitor systems until something needs attention. Kiro Crew Apps tailor that experience to a specific job, combining a purpose-built interface with agents, skills, schedules, integrations, and backend services.

Quick start · Build from source · Why Kiro Crew · Capabilities · How it works · Security · Install · Telemetry · Docs

Quick start

You choose how to run Kiro Crew: the desktop app with automatic updates, a
one-line install on your machine or a remote host, the Docker image for
always-on servers, or a build from source. Every path runs on kiro-cli
underneath, so the first launch installs it if needed and guides Kiro
device-code sign-in.

App downloads

The desktop app starts a bundled Gateway when no local Gateway is already
running, updates itself on the channel you download, and can connect to a
remote Gateway over an SSH tunnel. See the
desktop app guide.

• macOS: Stable | Insider | Nightly
• Linux: Stable | Insider | Nightly
• Windows: no desktop build yet, so run the Gateway from a source install and open the dashboard in your browser

One-line install

Install the prebuilt, SHA-256-verified wheel from the release CDN without
cloning the repository or running npm and a local build.

Stable, the default:

curl -fsSL https://download.crew.kiro.dev/cli.sh | sh

Track a faster channel, insider or nightly:

curl -fsSL https://download.crew.kiro.dev/cli.sh | sh -s -- --channel insider

Pin an exact version:

curl -fsSL https://download.crew.kiro.dev/cli.sh | sh -s -- --version 0.1.0

Open http://localhost:5476 and start a conversation. The web dashboard works
without messaging credentials. Add Slack,
Telegram, or
WeCom when you want to continue
working with the same agent away from the dashboard. These channels connect
outbound, so you do not need to expose the dashboard port publicly.

Docker

For always-on servers, the Gateway ships as a public multi-arch image on GHCR:

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

See the Docker guide for first-run login, channel tags, and
the container security model.

Build from source

macOS and Linux require Python 3.10+, Node.js 18+, npm, and
kiro-cli. The first desktop or dashboard launch
can install Kiro CLI on the Gateway host and guide device-code sign-in before
chat opens. Windows is supported through a native source install; follow the
Windows guide instead of the shell steps below.

# 1. Clone and build Kiro Crew
git clone https://github.com/kirodotdev/KiroCrew.git
cd KiroCrew
make build
source .venv/bin/activate

# 2. Configure, verify, and start
kirocrew setup
kirocrew doctor
kirocrew gateway

Why Kiro Crew

Most agent sessions end when the chat closes. Kiro Crew runs continuously on
hardware you control and keeps working between conversations.

Persistent. Sessions, memory, schedules, and task checkpoints survive
Gateway restarts, and scheduled or reactive work continues without someone at
the terminal.

Self-learning. Corrections and task failures become durable lessons.
Preferences and project context carry into new sessions.

Self-evolving. Repeated patterns become reusable skills. Memory, lessons,
and skills stay visible and editable, so each Kiro Crew grows more tailored to
the person and work around it.

Runs where you choose. Your Mac, a local container, or a remote machine
you control.

One Gateway, many surfaces. Work directly in the desktop app or web dashboard,
or continue the same work from the CLI and messaging surfaces like Slack and
Discord.

What Kiro Crew does

You can also paste a screenshot and ask what is causing an error. Kiro Crew sends
the image to the active Kiro model and keeps the diagnosis in the conversation
history.

The complete inventory is in Features and
What's New.

How it works

flowchart TD
    S["Desktop app · Web dashboard · Slack · Telegram · WeCom · CLI"]
    G["Gateway<br/>access · sessions · memory · schedules · approvals · apps"]
    A["Agent sessions<br/>ACP runtime · kiro-cli · MCP tools · models"]
    S --> G --> A

The Gateway separates where the agent runs from where you work with it. In the
desktop app or web dashboard, you can work directly through parallel conversations,
files, task runs, approvals, memory, and apps. From Slack, Telegram, WeCom, or
the CLI, the Gateway routes your work to managed agent sessions under the same
memory, tool, approval, and policy services. Apps extend the dashboard and
Gateway APIs with focused workflows.

Each active conversation or background task uses an agent session. Its session
provider drives kiro-cli over ACP, streams model and tool events, and preserves
conversation state. Depending on the workload, a session is backed by its own
ACP process or by a session handle on a shared multiplexed ACP runtime. The
Gateway manages these sessions along with scheduling, approvals, memory,
security policy, messaging connections, and the dashboard.

The current runtime places the Gateway, agent sessions, ACP processes, and state
on the same host. Run Kiro Crew on your Mac, inside a container on your machine,
or on a remote Linux host you control. Conversation history, memory, and
knowledge indexes remain on that host. Model requests are handled by kiro-cli
and follow the account and model configuration you use there.

Gateway. The Gateway is the long-running Kiro Crew process. It routes
messages from the desktop app, web, CLI, and the messaging surfaces listed below. It persists
session state, injects memory and skills, starts scheduled work, coordinates
subagents, brokers approvals, enforces runtime policy, and exposes activity in
the dashboard.

Agent sessions. A dashboard conversation or Slack thread maps to an isolated
agent session. Scheduled jobs, task runs, Telegram and WeCom conversations, and
subagents also use managed sessions. These sessions preserve conversation
context and can run concurrently before returning results to a parent session or
configured surface.

ACP runtime and turns. Kiro Crew supports both a dedicated kiro-cli ACP
process for a session and a shared ACP runtime that multiplexes multiple session
handles. During each turn, the session sends a prompt, streams model and tool
events, resolves approvals, and returns the final result. An agent session is a
logical isolation boundary, not necessarily one OS process.

Use the surface that fits the moment.

Choose how work starts.

Memory, learning, and evolution. Kiro Crew maintains preferences, active
project context, decaying history summaries, and durable lessons. Corrections
and task failures can change later behavior, while repeated patterns can become
reusable skills. In-process embeddings add semantic retrieval for memory and
the knowledge library. The stored state remains inspectable and editable
from the dashboard. Incognito and temporary session modes let you opt out when
a conversation should not persist.

Skills, MCP, and apps. Markdown skills supply reusable workflows and can be
loaded only when relevant. The built-in kirocrew-core and kirocrew-cron MCP
servers expose task, subagent, learning, messaging, and scheduling tools. You
can discover additional MCP servers from Kiro or Kiro Crew configuration. The
App Kit adds installable interfaces and domain workflows. Apps can add dashboard
pages, use scoped Gateway APIs, subscribe to events, and register lifecycle
hooks.

Security and control

Kiro Crew gives an AI agent real tool access, so the controls are enforced at
the runtime boundary instead of relying only on prompt instructions.

• Local by default. The dashboard binds to loopback unless you explicitly
  configure a network URL. Remote dashboards require token authentication.
• Interactive approvals. Review tool requests in the dashboard, Slack, or
  Telegram. Session-scoped trust can reduce repeated prompts without changing
  the underlying deny and sensitive-path controls.
• OS sandbox. On Linux and macOS, kiro-cli can run inside namespace or
  Seatbelt isolation. Standard, strict, and off modes make the tradeoff
  explicit. Windows does not currently provide this OS-level layer.
• Sensitive data guards. Kiro Crew blocks direct access to protected paths,
  strips sensitive environment variables, and redacts credential patterns from
  output before it reaches a chat surface.
• Denied operations. 137 bundled deny patterns block destructive commands and
  common exfiltration paths even when a session has broad approval.
• Auditability. Security events and tool activity are recorded for review.
  Use kirocrew security events, audit, and verify to inspect them.
• Governance ceiling. Optional policy and profile files compose with a
  tightest-wins model. A running app or agent can narrow the allowed scope but
  cannot loosen the enterprise ceiling. Inspect it with kirocrew policy show,
  validate, and explain.

No agent security layer removes the need to protect credentials and review
high-impact actions. Avoid pasting secrets or sensitive personal data into a
chat. Read the security architecture and use
SECURITY.md for private vulnerability reporting.

Install, configure, and operate

Installer details. The installer resolves the channel feed, verifies the wheel's SHA-256 against
the published manifest, installs through pipx when available or a managed
virtual environment at ~/.kiro/crew/venv, and records the channel in
~/.kiro/crew/channel. The channels are stable, insider, and nightly, and
KIROCREW_CHANNEL sets the default.

Pin an exact wheel. You can also install one exact wheel directly and pin it to its published
SHA-256. Every version directory publishes a SHA256SUMS file next to the
wheel, so take the hash for your wheel from there and put it in the URL
fragment. pip verifies the hash and does not consult a package index for
Kiro Crew itself:

pip install "https://download.crew.kiro.dev/cli/stable/<version>/kirocrew-<version>-py3-none-any.whl#sha256=<sha256>"

Semantic memory. Semantic memory needs no setup. Embeddings run in-process, and the Gateway
downloads its embedding model in the background on first start, verifies it,
and stores it under ~/.kiro/crew/models. Until the model lands, memory search
falls back to keyword search and picks up embeddings automatically without a
restart. Set KIROCREW_EMBED_MODEL_URL to point at a mirror for airgapped
installs.

See Installing and Building for wheels, desktop builds,
Windows, optional voice dependencies, and manual setup.

Choose where Kiro Crew runs. The current deployment model keeps the Gateway,
agent session runtime, ACP processes, and state together on one host. Your Apps
and chat surfaces connect to that Gateway.

For containers, mount the directory selected by KIROCREW_HOME so sessions,
configuration, memory, and credentials survive replacement. Keep the Gateway
port bound to loopback unless you intentionally configure authenticated remote
access. Container isolation and the Kiro Crew OS sandbox are separate layers
and depend on the host runtime configuration. See the
Docker guide for the published image and deployment details.

Keep it running. Install a systemd service on Linux or a launchd agent on
macOS:

kirocrew service install
kirocrew service status
kirocrew logs

The desktop app can use this local Gateway or connect to a remote one. For an
always-on VPS, home server, or cloud VM in your account, follow the
remote host guide. Kiro Crew does not require a
Kiro Crew-hosted control plane.

Configure it. User data lives under ~/.kiro/crew by default. Manage the
main configuration with kirocrew config get, set, and edit.

{
  "agent": {
    "provider": "acp",
    "approval_mode": "interactive",
    "sandbox": "auto"
  },
  "session": {
    "timeout_secs": 1800,
    "pool_size": 2
  },
  "dashboard": {
    "bot_name": "Kiro Crew"
  }
}

agent.provider is fixed to acp. Kiro Crew drives kiro-cli over the Agent
Client Protocol. Set the dashboard port with KIROCREW_PORT or
kirocrew gateway --port <n>. Slack credentials live in ~/.kiro/crew/.env
rather than the JSON config.

Troubleshoot quickly. Start with kirocrew doctor. For an ACP timeout,
confirm kiro-cli is on PATH and logged in, then allow extra time for the
first MCP startup. For memory search, check that the embedding
model finished downloading under ~/.kiro/crew/models. For a stale MCP configuration, run
kirocrew setup --agent-only, or add --clean to rebuild it.

Anonymous usage telemetry

Kiro Crew sends one anonymous heartbeat per day so maintainers can see how
many copies are actively running, which versions are in use, and which
platforms and install channels to support. After a successful install or update
from the official app catalog, it also sends one anonymous per-app receipt.
Both signals are on by default and use the same controls below.

To turn it off, flip Settings → Privacy → Send anonymous usage heartbeat in
the dashboard (the same switch appears on the last step of first-run
onboarding). Or from a terminal:

kirocrew telemetry disable        # persists to config.json
export KIROCREW_TELEMETRY_DISABLED=1   # or per-shell / per-container
kirocrew telemetry status         # print exactly what would be sent

The toggle and kirocrew telemetry disable write the same setting, so either
one sticks across restarts and upgrades. KIROCREW_TELEMETRY_DISABLED overrides
both — when it is set, the dashboard toggle is disabled and says so.

Exactly these five fields are sent, at most once per day, and nothing else:

Official-app install receipts are separate and event-based. After a
successful official-catalog install or update, Kiro Crew sends one GET to
/b/1/install/<app-slug>?t=<token>&k=<fresh|update>&v=<release> on the same
telemetry host. The slug is the public catalog identifier. t is the first 32
hex characters of HMAC-SHA256 keyed by the local beacon install id over
app-install:<slug>; the raw install id is never sent, and tokens for different
apps cannot be linked to assemble an installed-app profile. k separates fresh
installs from updates, and v is the same release-only Kiro Crew version clamp
used by the heartbeat.

Receipts are emitted only for bundled or edition-provided official catalog
entries. Apps from user-configured registries, local-directory installs, and
self-registered apps emit nothing, so private app names never leave the machine.
If no persistent beacon install id exists yet, the receipt is skipped.

This list used to be nine fields. Release channel, OS, CPU architecture and
governance posture were removed — each was coarse on its own, but the
instance id is stable, so those attributes all describe the same copy and
together they narrowed the group any one install blends into far more than any
single field suggests.

We report this as Daily Active Crews rather than "users": Kiro Crew has
no account system of its own, and the Kiro sign-in that kiro-cli uses for
model access is never read or sent. There is no way to resolve a copy to a
person, so one person running Kiro Crew on three machines counts as three
Crews.

Never sent: your prompts, model responses, file contents, file paths, repo
or branch names, credentials, environment variables, hostname, username, or IP
address. The receiving CDN is configured not to log client IP addresses — the
log delivery does not include that field, so no IP is stored at all.

Automatically off in CI, and whenever KIROCREW_HOME points somewhere other
than ~/.kiro/crew (dev instances and pods are never counted).

Enterprise administrators can pin it off entirely. A capabilities.telemetry
entry in the security policy blocks both outbound signals regardless of the local
setting, and the dashboard toggle then says so instead of offering a change that
would not take effect:

{"version": 1, "boot": {"fail_closed": true},
 "capabilities": {"telemetry": {"enabled": false}}}

See docs/system-specs/modules/governance.md.

This is separate from telemetry.enabled, which controls local-only
performance metrics that never leave your machine. See
docs/system-specs/modules/metrics.md.

Docs and contributing

Contributions are welcome. Create a branch from main, keep changes focused,
and run the relevant checks before opening a pull request:

# Backend
pip install -e ".[voice]" --group dev
pytest

# Frontend
cd website
npm ci
npm run check
npm run build

Use GitHub Issues for bugs and
feature requests. Do not file security vulnerabilities publicly.

Contributors

Kiro Crew was made possible by its internal community, the people who supported the
project and shipped its code, together with everyone who has since opened a pull
request in the open. This is that founding group; as Kiro Crew grows in the open, we
look forward to many more contributors joining them. Thank you to everyone who helped
make this tool possible:

Listed alphabetically by GitHub username. Internal contributors appear here if they
consented to public recognition in the contributor survey; open-source contributors are
included from this repository's pull request history. If you contributed and would like
to be added, corrected, or removed, please open an issue or a pull request.

License

Kiro Crew is licensed under the Apache License 2.0. See
NOTICE for attribution information.