by agynio
Agyn is an open-source Kubernetes-native runtime that moves AI agents like Claude Code and Codex from laptops to company infrastructure with the controls enterprises need.
# Add to your Claude Code skills
git clone https://github.com/agynio/platformLast scanned: 5/30/2026
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}platform is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by agynio. Agyn is an open-source Kubernetes-native runtime that moves AI agents like Claude Code and Codex from laptops to company infrastructure with the controls enterprises need. It has 207 GitHub stars.
Yes. platform passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.
Clone the repository with "git clone https://github.com/agynio/platform" and add it to your Claude Code skills directory (see the Installation section above).
platform is primarily written in TypeScript. It is open-source under agynio on GitHub, so you can review or fork the full source.
Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh platform against similar tools.
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You built the agent. Now how do you let the rest of the company use it — without exposing secrets, blowing budgets, or losing control? Agyn is an open-source, Kubernetes-native agent orchestration platform. Run any AI agent (Claude Code, Codex, custom) at scale with serverless execution, Terraform-managed configuration, and zero-trust networking where credentials never reach the LLM context.
| Problem | Agyn |
|---|---|
| Agents run on individual laptops | Centralized deployment on your infrastructure |
| Secrets passed directly to models | Secrets isolated, never exposed to the model |
| No budget visibility or limits | Spend caps at any level — per agent, per team, per org |
| No access control | RBAC, SSO, audit logs |
| Locked to one vendor | Agent-agnostic, model-agnostic |
| Can't scale | Horizontal scaling, auto-termination on idle |
An open-source, self-hosted alternative to Google AX, AWS Bedrock AgentCore, and Claude Code Cloud for running AI agents in production with full control over security and configuration.
| Capability | Agyn | Google AX | AWS AgentCore | Claude Code Cloud | kagent | Copilot Studio |
|---|---|---|---|---|---|---|
| Self-hostable | ${\color{green}✓}$ | ${\color{green}✓}$ | ${\color{red}✗}$ | ${\color{red}✗}$ | ${\color{green}✓}$ | ${\color{red}✗}$ |
| Run any agent container | ${\color{green}✓}$ | ${\color{red}✗}$ | ${\color{green}✓}$ | ${\color{red}✗}$ | ${\color{red}✗}$ | ${\color{red}✗}$ |
| Declarative config (IaC) | ${\color{green}✓}$ (Terraform) | ${\color{green}✓}$ (YAML) | ${\color{red}✗}$ | ${\color{red}✗}$ | ${\color{green}✓}$ (CRDs) | ${\color{red}✗}$ |
| Serverless (scale-to-zero) | ${\color{green}✓}$ | ${\color{green}✓}$ | ${\color{green}✓}$ | ${\color{green}✓}$ | ${\color{red}✗}$ | ${\color{green}✓}$ |
| MCP servers isolation | ${\color{green}✓}$ | ${\color{red}✗}$ | -- | -- | ${\color{red}✗}$ | -- |
| Secrets never reach LLM | ${\color{green}✓}$ | ${\color{red}✗}$ | -- | -- | ${\color{red}✗}$ | -- |
| Zero-trust networking | ${\color{green}✓}$ | ${\color{red}✗}$ | ${\color{red}✗}$ | ${\color{red}✗}$ | ${\color{red}✗}$ | ${\color{red}✗}$ |
| Per-conversation sandboxing | ${\color{green}✓}$ | ${\color{green}✓}$ | ${\color{green}✓}$ | ${\color{green}✓}$ | ${\color{red}✗}$ | ${\color{green}✓}$ |

git clone --branch latest https://github.com/agynio/bootstrap.git
cd bootstrap
./apply.sh
Open the console. Create an org. Deploy your first agent.
Want a ready-made fleet to play with? Apply agynio/demo-agent — a Terraform config that provisions a support, marketing, and data-engineer agent in one command.
For production installs, see Self-host install.
Stop clicking. Version your agent infrastructure.
resource "agyn_agent" "support" {
organization_id = agyn_organization.acme.id
name = "Support"
nickname = "support"
model = agyn_llm_model.gpt_4o.name
image = "ghcr.io/agynio/agent-runtime:v1.0.0"
init_image = "ghcr.io/agynio/agent-init-codex:v1.0.0"
idle_timeout = "5m"
availability = "internal"
}
resource "agyn_agent_mcp" "zendesk" {
agent_id = agyn_agent.support.id
name = "zendesk"
image = "ghcr.io/acme/zendesk-mcp:latest"
envs = [
{
name = "ZENDESK_TOKEN"
secret_id = agyn_secret.zendesk_token.id
},
]
}
terraform init && terraform apply
See the Terraform provider reference for every resource.
Full architecture: docs/operate/architecture.md.
| Video | What it shows |
|---|---|
| Agyn in 3 minutes — From clean cluster to a working agent answering a chat message. End-to-end tour. | |
| Coming soon | Deploying agents with Terraform — Define an agent fleet as code, apply it, talk to them. |
| Coming soon | Inspecting a run with Tracing — Every LLM call, every tool execution, every context decision. |
Full docs live in docs/:
Agyn is split across focused repositories. The most useful starting points:
| Repo | What it is |
|---|---|
agynio/platform |
This repo. Documentation hub. |
agynio/architecture |
Source-of-truth architecture and product specs. |
agynio/bootstrap |
One-command local install (k3d + Terraform). |
agynio/platform-charts |
Production Helm charts. |
agynio/api |
Protobuf schemas for every service. |
agynio/terraform-provider-agyn |
Terraform provider. |
agynio/agyn-cli |
Platform CLI. |
agynio/console-app · chat-app · tracing-app |
Browser UIs. |
agynio/agent-init-codex · agent-init-claude · agent-init-agn |
Agent CLI init images. |
Full list with descriptions: docs/reference/service-catalog.md.
Good places to start:
AGPL-3.0