A Kubernetes-native control plane for AI agent instance management, with governed AI access, runtime orchestration, and reusable resources across multiple agent runtimes.
Languages: English | Chinese | Japanese | Korean | Deutsch
Explore the Product | AI Gateway | Agent Control Plane | Resource Management | Get Started
A quick look at fast agent provisioning, skill management and scanning, and AI Gateway governance.
Recent highlights from the latest product and documentation updates.
- [2026-04-08] Added skill management and skill scanning workflows to the platform, via Merged PR #52.
- [2026-03-26] AI Gateway documentation was refreshed with stronger coverage for model governance, audit and trace, cost accounting, and risk control. See the AI Gateway Guide.
- [2026-03-20] ClawManager evolved into a broader control plane for AI agent workspaces, with stronger runtime control, reusable resources, and security scanning workflows.
If ClawManager is useful to your team, please star the project to help more users and contributors discover it.
ClawManager brings AI agent instance operations to Kubernetes and layers three higher-level control planes on top of that runtime foundation. Teams use it to govern AI access, orchestrate runtime behavior through agents, and manage reusable channels and skills with scanning and bundle-based delivery.
It is designed for:
- platform teams running AI agent instances for multiple users
- operators who need runtime visibility, command dispatch, and desired-state control
- builders who want governed AI access and reusable resource injection instead of manual per-instance setup
ClawManager now has clearer entry points for both full Kubernetes deployments and lightweight cluster setups. If you want to evaluate the product quickly, start with the guide that matches your environment and then follow the first-use walkthrough.
- Standard Kubernetes deployment: deployments/k8s/clawmanager.yaml
- K3s or lightweight deployment: deployments/k3s/clawmanager.yaml
- Operations-oriented quick start and first login flow: User Guide
- Deployment notes and architecture-level context: Deployment Guide
AI Gateway is the governance plane for model access inside ClawManager. It gives managed agent runtimes a unified OpenAI-compatible entry point while adding policy and audit controls on top of upstream providers.
- Unified gateway entry for model traffic
- Secure model routing and policy-aware model selection
- End-to-end audit and trace records
- Built-in cost accounting and usage analysis
- Risk control rules that can block or reroute requests
See the AI Gateway Guide.
Agent Control Plane is the runtime orchestration layer for managed AI agent instances. It turns each instance into a managed runtime that can register, report status, receive commands, and stay aligned with platform-side desired state.
- Agent registration with secure bootstrap and session lifecycle
- Heartbeat-driven runtime status and health reporting
- Desired-state synchronization between the control plane and the instance
- Runtime command dispatch for start, stop, config apply, health checks, and skill operations
- Instance-level visibility into agent status, channels, skills, and command history
See the Agent Control Plane Guide.
Resource Management is the reusable asset layer for AI agent workspaces. It helps teams prepare channels and skills once, organize them into bundles, inject them into instances, and keep security review in the loop.
- Channel management for workspace connectivity and integration templates
- Skill management for reusable packaged capabilities
- Skill Scanner workflows for risk review and scan operations
- Bundle-based resource composition for repeatable workspace setup
- Injection snapshots and runtime-level visibility into what was applied
See the Resource Management Guide and the Security / Skill Scanner Guide.
The product is designed to feel coherent across administration, workspace access, and AI governance. Instead of treating these as separate tools, ClawManager brings them into one control surface.
The admin console brings together users, quotas, runtime operations, security controls, and platform-level policies in one place. It is the operational center for teams running AI agent infrastructure at scale.
The portal experience gives users a clean entry point into their workspaces, with browser-based access and runtime visibility that stays connected to the control plane instead of exposing infrastructure details directly.
AI Gateway extends the workspace experience with governed model access, audit trails, cost visibility, and risk-aware routing, making AI usage manageable as part of the platform rather than an isolated integration.
- Admins define governance policies and reusable resources.
- Users create or enter managed AI agent workspaces on Kubernetes.
- Agents connect back to the control plane and report runtime state.
- Channels, skills, and bundles are compiled and applied to instances.
- AI traffic flows through AI Gateway with audit, risk, and cost controls.
ClawManager is built as a Kubernetes-native platform with a React frontend, a Go backend, MySQL for state, and supporting services such as skill-scanner and object storage integrations. The repository is organized around product subsystems rather than a single monolith page, so the best developer experience is to start from the relevant guide and then move into the code.
- Frontend app and admin/user surfaces live under
frontend/ - Backend services, handlers, repositories, and migrations live under
backend/ - Deployment assets live under
deployments/ - Supporting product docs live under
docs/
See the Developer Guide.
- User Guide
- Deployment Guide
- Admin and User Guide
- Agent Control Plane Guide
- AI Gateway Guide
- Security / Skill Scanner Guide
- Resource Management Guide
- Developer Guide
This project is licensed under the MIT License.
Issues and pull requests are welcome.