Deploy, orchestrate, and scale AI agents across your infrastructure.
One binary. No dependencies. From laptop to cluster.
curl -fsSL https://klaw.sh/install.sh | shFrom local development to production clusters, klaw handles the infrastructure so you can focus on your agents.
One ~20MB binary. No Python, no Docker, no dependencies. Just download and run.
Familiar commands: get, create, delete, describe, dispatch.
Claude, GPT-4, Gemini, Llama, DeepSeek via each::labs Router or OpenRouter.
Slack, CLI, TUI, REST API. Deploy agents where your team works.
Controller-node architecture. Scale from laptop to enterprise cluster.
Kubernetes-style multi-tenancy. Isolate teams, projects, and environments.
Schedule recurring agent tasks. Automate reports, monitoring, and workflows.
Composable capability bundles. web-search, git, docker, database, and more.
Run agents in isolated Podman containers for security and reproducibility.
Inspired by Kubernetes, klaw brings familiar multi-tenancy patterns to AI agent orchestration. Isolate teams, projects, and environments with first-class namespace support.
Each team gets their own namespace with isolated agents, secrets, and resources. No cross-contamination.
$ klaw create namespace team-backend$ klaw create namespace team-frontend$ klaw create namespace team-data
Run dev, staging, and production environments on the same cluster with complete isolation.
$ klaw create namespace dev$ klaw create namespace staging$ klaw create namespace prod$# Deploy to specific environment$ klaw dispatch -n prod "analyze logs"
Set limits per namespace to control costs and prevent runaway agents from consuming all resources.
# Coming soon$ klaw set quota team-ml --max-tokens 1M/day$ klaw set quota team-ml --max-agents 10
Fine-grained access control. Users can only access namespaces they are authorized for.
# Switch namespace context$ klaw config set-context --namespace=team-backend$# List agents in current namespace$ klaw get agents
klaw borrows the best ideas from Kubernetes—namespaces, declarative configs, kubectl-style CLI—but is purpose-built for AI agents. No container orchestration overhead.
| Feature | klaw | Kubernetes |
|---|---|---|
| Installation | Single binary (~20MB) | Complex multi-component setup |
| Learning Curve | Minutes to get started | Weeks/months to master |
| Resource Usage | ~50MB RAM idle | 2GB+ for control plane |
| Namespaces | Built-in multi-tenancy | Built-in multi-tenancy |
| CLI Experience | kubectl-inspired, familiar | kubectl (the original) |
| Declarative Config | YAML manifests | YAML manifests |
| Focus | AI Agents & LLMs | Container orchestration |
| Built-in LLM Support | 300+ models ready | Requires custom setup |
Why not just use Kubernetes? Kubernetes is amazing for container orchestration, but it is overkill for AI agents. klaw gives you the patterns you love—namespaces, declarative YAML, familiar CLI—without the complexity of running a full K8s cluster. Think of it as "Kubernetes for AI Agents."
One binary. No dependencies. No configuration needed.
From local development to enterprise clusters. Same commands, same agents.
klaw chat klaw start
Interactive chat or full platform with Slack integration. Zero config required.
klaw controller start klaw node join :9090 klaw dispatch "task"
Controller-node architecture. Dispatch tasks across multiple machines.
klaw build klaw run agent --task klaw ps
Run agents in Podman containers for security and reproducibility.
Get started in under a minute. No account required.
curl -fsSL https://klaw.sh/install.sh | sh