Agyn

Ship AI agents to your company. Safely.

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 platform that moves agents from laptops to company infrastructure with the controls enterprises need.

Why Agyn

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

Getting Started

Deploy a cluster in 15 minutes

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.

Define agents as code

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.

How it works

Each agent is a first-class citizen:

• Isolated sandbox — own container, filesystem, env vars, secrets
• MCPs in separate containers — full process isolation per tool
• Observability built in — token usage, compute, activity logs
• Auto-scaling — agents spin up on demand, terminate on idle

Full architecture: docs/operate/architecture.md.

Video walkthroughs

Video	What it shows
	Agyn in 5 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.

Documentation

Full docs live in docs/:

• Introduction — what Agyn is, concepts, architecture at a glance.
• Self-host install — bootstrap, production install, upgrades.
• Administer — Console + Terraform for orgs, agents, models, secrets, runners, apps.
• Use — chat, files, tracing, usage, port exposure.
• Build & extend — Gateway API, MCP servers, agent CLIs, apps.
• Operate — networking, identity, scaling, backups, security.
• Reference — glossary, service catalog, schema pointers.
• Troubleshooting — diagnostic playbook by symptom + FAQ.

Repository map

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.

Community

• Website
• Blog
• Discord

Contributing

Good places to start:

• Read the architecture docs to understand the system before touching code.
• Join the Discord for questions while you work.

License

AGPL-3.0