Crew44
Orchestrate the coding agents already on your machine into a specialist team, each bound to the model that fits its role.
- Source repo
- getcrew44/crew44
- Stars
- ★ 358
- Last updated
- 4mo ago
- License
- MIT
- Primary language
- Go
- FA score
- 42/100 · Major gaps
At a glance
- How it runs
- Works with
- Universal · cross-platformCodex · Claude CodeChatGPT (Partial support)
- Cost
- Free software; you pay for model usage
- Setup effort
- Medium · a few setup steps
- You'll need
- Typical use
- Developers who already run Claude Code and Codex and want planning, coding and review done by different models
- Not a fit if
- Solo users who just want one generalist coding agent
- Users who want a zero-install, browser-only tool
- Teams unwilling to depend on third-party coding CLIs and their accounts
- Source review
- 42/100 · Major gaps
What does this agent do, and when should you use it?
Crew44 is a local-first desktop orchestrator that turns existing coding-agent CLIs into a coordinated crew. An Electron + React 19 renderer talks over WebSocket JSON-RPC to a Go daemon bound to 127.0.0.1; the daemon discovers installed runtimes (Claude Code, Codex, Cursor Agent, Gemini CLI, OpenCode, Qwen Code and more), routes turns to them as subprocesses, and persists everything as plain files under ~/.crew44/. You define Agents — a persona bound to one runtime and model with an instruction and attached skills — and skills are file-based SKILL.md bundles injected into the session across providers. Handover markers pass a turn to a teammate with a one-line brief, optional Worktrees run a task on its own crew/… git branch, and an optional Goal locks a criteria checklist that an independent verifier in a fresh session must confirm. The default crew ships with a Partner, an Engineer, a Product Lead and a Designer. A companion Expo app pairs over an end-to-end encrypted Noise tunnel via a self-hostable relay.
On launch the Go daemon scans disk for installed coding-agent CLIs and exposes runtime discovery, agent/skill/chat state, and an event stream over WebSocket JSON-RPC, authenticated with a per-launch bearer token (only /health is open). In the Crew view you bind each Agent to a runtime, model, instruction and skills folder; a Skill is a SKILL.md plus assets stored in one shared directory that works across every provider. Starting a chat spawns the chosen CLI, streams turn events into an append-only events.jsonl, and runs one in-flight response at a time. Agents emit Handover markers to pass the baton with a short brief. Toggling Worktree gives the chat an isolated git checkout on a crew/… branch without touching your working tree; setting a Goal makes the crew scope a locked criteria checklist and requires a fresh-session verifier to confirm each item before sign-off. The renderer covers Crew, Tasks, New Task, Auto suggestions and Onboarding; daemon config comes from HOST/PORT, AUTH_TOKEN and CREW44_STATE_DIR.
- Developers who already run Claude Code and Codex and want planning, coding and review done by different models
- Teams that need project memory and shared SKILL.md workflows so conventions persist across tasks
- Anyone who wants an agent to complete and verify a task on an isolated branch without disturbing the main working tree
- Quality-sensitive work where an independent verifier must confirm a locked checklist before you accept the result
- Mobile users who want to read or nudge a running local crew from their phone
How do you install or deploy this agent?
Signed desktop builds are offered free with no account:
macOS (Apple Silicon) .dmg
Windows (x64) .exe installer
Linux (ARM64) .AppImage / .debDownloads are at crew44.io/download. To build from source you need macOS, Windows or Linux, Node 20+, Go 1.26+, and at least one coding-agent CLI installed:
npm install
npm run devThat builds the Go daemon, starts Vite, launches Electron and connects the renderer once the daemon reports healthy.
How do you use this agent?
Configure the daemon with environment variables:
HOST=127.0.0.1 PORT=8080 AUTH_TOKEN=<token> CREW44_STATE_DIR=~/.crew44 npm run devWith auth enabled, /rpc requires WebSocket subprotocols:
new WebSocket("ws://127.0.0.1:8080/rpc", [
"crew44.rpc.v1",
`crew44.bearer.${token}`,
])In the app, confirm the detected runtimes on the Crew page, bind models and skills folders to the Partner, Engineer and other agents, then create a task from Tasks with optional Worktree or Goal settings. Other scripts:
npm run build # renderer build + local app
npm run web:dev # daemon + bare Vite dev server
npm run test # Go, renderer and mobile tests
npm run clean # remove local build artifactsWhat are this agent's strengths and limitations?
- Runtime layer is a small Go interface: add an adapter under daemon/internal/backendagent/ and it appears in the picker, so you are not locked to one provider
- All state lives as plain files under ~/.crew44/ with an append-only events.jsonl, which is easy to inspect and back up
- Handovers carry a one-line brief instead of full context, keeping multi-role chats leaner
- Worktree toggle runs a task on an isolated crew/… branch so your working tree stays clean
- Goal sign-off uses a verifier in a fresh session with no chat history, reducing self-review bias
- Requires at least one installed and authenticated third-party coding-agent CLI; Crew44 supplies no model of its own
- Building from source needs both Node 20+ and Go 1.26+ toolchains plus a daemon compile step
- Mobile pairing relies on a relay for NAT traversal, so remote access is not purely local
- The optional headless browser pulls Playwright and Chromium via npm, adding network and disk cost
How does this agent compare with similar options?
Key facts side by side with the most closely related agents.
| Agent | Source review | Form / cost | Stars | Updated | Language | Full support on |
|---|---|---|---|---|---|---|
| Crew44 This agent | 42 · Major gaps | Desktop appFree + model costs | ★ 358 | 4mo ago | Go | Codex · Claude Code |
| Munder Difflin – Multi-Agent Office Floor | 43 · Major gaps | Desktop appFree + model costs | ★ 9.4k | today | JavaScript | ChatGPT · Codex · Claude Code |
| wsp | 39 · Major gaps | Desktop appFree + model costs | ★ 14 | today | TypeScript | Codex · Claude Code |
| Yardlet | 49 · Major gaps | Desktop appFree | ★ 31 | today | Swift | Codex · Claude Code |
How does FollowAgents rate this agent?
Why each dimension lost points
README states the daemon binds 127.0.0.1, uses a per-launch bearer token, and only /health is unauthenticated, with plain-file state under ~/.crew44 — decent data-flow transparency (2). However empty AUTH_TOKEN falls back to dev mode (weak default); the agent spawns external CLIs and an on-demand headless browser visiting arbitrary URLs with no least-privilege or user-confirmation evidence (least_privilege/user_confirmation 1 each); sensitive data handling relies on plaintext local files with no encryption/redaction notes (1); dependency security shows only version ranges in package.json with no audit or lockfile evidence (1); external effects (browser, mobile relay) are described but no rollback/revocation mechanism (external_effects/rollback 1 each); source attribution is only README/LICENSE naming with unverified publisher (1).
Architecture diagram, concept table, package.json scripts and CI workflow are mutually consistent (self_consistency 2). Dependency availability rests on npm install and Go 1.26+/Node 20+ declarations without lockfile or offline plan (1). Failure messages: README describes no error handling or diagnostics (1).
Targets multiple runtimes, platforms, desktop and mobile with clear scenarios (audience_and_scenarios 2); environment fit covers macOS/Windows/Linux and many CLIs (environment_fit 2). But capability boundaries (what tasks are unsuitable, agent permission scope) and trigger precision (handover, goal verification conditions) are only conceptual (1 each).
README is well-structured with project layout and dev commands (information_architecture 2); install steps and prerequisites are clear (install_notes 2); LICENSE is full MIT text (license 3). Naming stability, examples/FAQ, known limitations, versioning (only a CHANGELOG.md link with no content) and maintenance responsibility (author email, unverified publisher) are thin (1 each).
Output usability, marginal value and cost-benefit are supported only by marketing-style README claims (e.g. 'skills that compound', 'right model per role') with no verifiable output samples or benchmarks (1 each).
README claims partially corroborate with CI workflow and package.json scripts (cross_source_corroboration 1), but most capability claims lack corresponding code or test evidence (claim_traceability 1), and fact vs inference is not clearly separated (fact_inference_separation 1).
- Empty AUTH_TOKEN falls back to dev mode, potentially exposing the local daemon unauthenticated on 127.0.0.1; confirm production defaults.
- The agent spawns external CLIs and a headless browser visiting arbitrary URLs with no least-privilege or user-confirmation evidence.
- State is stored as plaintext files under ~/.crew44 with no encryption or redaction described.
- Publisher identity is unverified; maintenance responsibility and update path are unclear.
- README is largely marketing claims without verifiable output samples or benchmarks.