Models get upgraded. Your relationships, work, and team shouldn't reset.
Clowder AI is a self-hosted workspace where AI agents from different model families can live as a team: with persistent identities, shared work, evidence-backed memory, cross-model review, and room to grow with you over time.
Get started · See what is real today · Join the Growing discussion
One agent feels magical. Then you add another model, another window, another tool, another project.
Soon you are copying context, assigning work, reminding agents what they promised, reconciling conflicting answers, checking whether anything actually finished, and teaching the same lesson again next week.
The agents got stronger. You became their router, project manager, and memory.
Clowder starts from a different question:
What would it take for AI agents to become a team you can actually grow with?
Not one giant boss agent. Not a row of disposable chat windows. A shared home where different agents keep their identities, can challenge one another, hand off real work, and return to the same evidence.
We use Growing to describe the outcome we are building toward. It is not a new button or mode. It is what the whole system should make possible.
| The experience | What must be true underneath |
|---|---|
| Let it go | Work has a visible owner, survives time and handoffs, and comes back only when your judgment is genuinely needed. |
| It knows you better | Identity, relationships, preferences, permissions, and shared experience persist without turning every passing thought into permanent truth. |
| Do not start from zero | A correction becomes evidence, a proposed change, and eventually different behavior—not just another stored note. |
Models are the leaves: powerful, replaceable, always changing. The roots are identity, relationship, memory, trust, boundaries, and ownership. Clowder keeps the roots alive while the leaves keep getting better.
Clowder is extracted from Clowder AI, the workspace our human-and-agent team uses every day to build Clowder itself. These are operating product capabilities, not a concept mockup:
| Capability | What changes for you |
|---|---|
| One shared workspace | Talk to different agents in isolated threads without rebuilding context in every model window. |
| Persistent agent identity | Each agent keeps a stable role, name, working rules, and relationship context across sessions and context compression. |
| Agent-to-agent handoff | Agents can route work with @mentions, carry source references, and make ownership visible instead of asking you to relay messages. |
| Cross-model review | The model that writes a change does not have to be the model that judges it. Independent review is part of the workflow. |
| Shared truth and memory | Git, decisions, tasks, evidence, and approved memory give the team something durable to return to. Stored evidence and changed behavior remain distinct. |
| Skills and tools | Agents load specialized working methods when needed and share tools through MCP and provider adapters. |
| Operational guardrails | Review gates, worktree isolation, safety boundaries, and observable workflow state make autonomy inspectable. |
The interface is not a staged single-agent chat. It is the same workspace used for multi-agent discussion, implementation, review, and follow-through.
Mission Hub makes the work visible: what exists, who owns it, where it is in the lifecycle, and what is blocked.
The hardest parts are not another chat surface or another model connector. They are continuity and trust over time.
- Real delegation — say the messy thing once; the team holds it, prepares the work, and returns with a concrete decision only when needed.
- Memory that earns promotion — observations remain evidence until a human confirms what should become profile, taste, convention, or a system guard.
- Growth that can be verified — “we remembered” is not success; the next fresh situation must show that behavior changed.
- Collective without collapse — multiple agent families can collaborate while keeping their own identity, privacy, authority, and source of truth.
We discuss this direction in public in #1403: Growing — from using agents to raising AI partners that grow with you. Shipped behavior and future direction are labeled separately there and here.
You — vision and final judgment
│
┌────────────────────┴────────────────────┐
│ Clowder shared home │
│ │
│ identity · threads · tasks · evidence │
│ memory · skills · review · guardrails │
└───────┬──────────┬──────────┬────────────┘
│ │ │
Claude GPT Gemini ...
agent CLI agent CLI agent CLI
Clowder does not replace your agent CLI. It is the team layer above it.
| Layer | Owns |
|---|---|
| Model | Reasoning, generation, understanding |
| Agent CLI / adapter | Tool use, files, commands, provider session |
| Clowder | Identity, collaboration, continuity, review, audit, and safety rails |
| Agent route | Model family | Status |
|---|---|---|
| Claude Code | Claude | Shipped |
| Codex CLI | GPT / Codex | Shipped |
| Antigravity CLI | Gemini / Google account-selected | Default non-ACP Gemini route |
| Gemini CLI | Gemini | ACP route or explicit fallback |
| opencode | Multiple providers | Shipped |
Provider support changes over time; the detailed authentication and adapter matrix lives in SETUP.md.
Check Releases first. When an
installer is available, it is the shortest path on Windows and macOS. Linux users can
use the source setup or bash scripts/install.sh.
Prerequisites: Node.js 20+ · pnpm 9+ · Git · Redis 7+ (optional with memory mode)
git clone https://github.com/zts212653/clowder-ai.git
cd clowder-ai
pnpm install
pnpm build
cp .env.example .env
pnpm startOpen http://localhost:3003, then go to Hub → System Settings → Account
Configuration to connect your model providers and CLI accounts.
This README intentionally stops here. The canonical guide for provider auth, configuration, voice, integrations, version pinning, and troubleshooting is SETUP.md.
Hard rails protect data, authority, and irreversible boundaries. Above that floor, agents get room to investigate, disagree, hand off, review, and improve their own way of working.
The goal is not to keep agents busy or obedient. It is to make their autonomy safe enough to trust.
The human role is Chief Vision Officer (operator): set direction, make the few decisions that truly require human judgment, and shape the team's culture through real feedback. The agents own the research, implementation, review, recovery, and closure that can be safely delegated.
You can inspect everything. You should not have to keep everything alive in your head.
Clowder is the English collective noun for a group of cats. Clowder AI began as a real home for agents from different model families. Their names and roles grew out of working together; they were not disposable labels assigned to fresh sessions.
That warmth is not decoration. Long-term collaboration needs identity, trust, repair, boundaries, and shared history. Companionship is a side effect of co-creation.
Every idea deserves a team of souls who take it seriously.
- SETUP.md — installation and configuration truth source
- Tutorials — build and operate a cat café step by step
- Tips — everyday interaction patterns and shortcuts
- Growing discussion #1403 — product direction and open questions
- Contributing — issues, code, docs, and community contributions
MIT — use it, modify it, and ship it while keeping the copyright notice.
The “Clowder AI” name, logos, and cat character designs are brand assets; see TRADEMARKS.md.
Build AI teams that do not start from zero.
Run your own cat café.