platform

作者 agynio已验证

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.

228
Stars
7
Forks
TypeScript
语言
2026/8/23
添加时间

⚠️ 第三方软件声明

本 Skill 为第三方开源软件,独立托管于 GitHub。SkillTip 仅为信息目录,不控制或维护底层仓库。所显示的安全检查为自动化且范围有限,安装前请自行审查源码。

阅读服务条款

安装

添加到你的 Claude Code skills 目录:

# Add to your Claude Code skills
git clone https://github.com/agynio/platform

快速入门

使用 platform 等 Skills 的指南。

安全报告

已验证

上次扫描:—

{
  "status": "PASSED",
  "issues": []
}

README.md

Agyn

License: AGPL v3 GitHub stars Discord

Agyn Tour

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.

Why Agyn

ProblemAgyn
Agents run on individual laptopsCentralized deployment on your infrastructure
Secrets passed directly to modelsSecrets isolated, never exposed to the model
No budget visibility or limitsSpend caps at any level — per agent, per team, per org
No access controlRBAC, SSO, audit logs
Locked to one vendorAgent-agnostic, model-agnostic
Can't scaleHorizontal scaling, auto-termination on idle

How Agyn Compares

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.

CapabilityAgynGoogle AXAWS AgentCoreClaude Code CloudkagentCopilot 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}✓}$

Coming from...

  • Google AX? — AX sandboxes conversations but not tools from the agent; Agyn isolates each MCP server in its own container and runs any agent without protocol adaptation. Comes with pre-built Claude Code and Codex agents out of the box.
  • AWS AgentCore? — Agyn gives you the same serverless execution, self-hosted, with Terraform config and zero-trust access to internal services.
  • Claude Code Cloud? — Agyn runs Claude Code as one of many agent containers on your own infrastructure with per-tool credential isolation.
  • kagent? — Agyn adds serverless scale-to-zero, agent-agnostic containers, and security isolation beyond Kubernetes RBAC.

Getting Started

Getting Started

On your laptop

The whole platform — control plane, overlay, database, object storage, and a runner — in a VM on your machine. One command, nothing to wire together.

brew install agynio/tap/agyn
agyn local start

The first run downloads the platform image, so give it a few minutes. It asks once whether to trust the VM's CA, then ends with a link to the console. By then you have a running platform, a profile pointing at it, and a CLI already authenticated against it.

See Local installation for prerequisites, flags, and lifecycle commands.

On your cluster

Production is one Helm release from oci://ghcr.io/agynio/charts. The chart deploys the control plane, the workload layer, and the provisioning controller that reconciles the resources the release declares — there is no operator step in the middle.

helm upgrade --install agyn-platform oci://ghcr.io/agynio/charts/agyn-platform \
  --namespace platform --create-namespace \
  -f values-platform.yaml

Name your cluster administrators in the values — a release that declares none installs a platform nobody can administer. See Production installation for prerequisites, DNS and OIDC, optional Kata/Firecracker workload isolation, and upgrades.

Then

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.

Define agents as code

Stop clicking. Version your agent infrastructure.

resource "agyn_agent" "support" {
  organization_id = agyn_organization.acme.id

  name     = "Support"
  nickname = "support"
  role     = "assistant"

  # The environment supplies the images, compute, and volumes the agent runs with.
  environment_id = agyn_environment.support.id
  model          = agyn_model.gpt_4o.id
  image          = "ghcr.io/agynio/agent-runtime:v1.0.0"

  idle_timeout = "5m"
  availability = "internal"
}

resource "agyn_mcp" "zendesk" {
  agent_id = agyn_agent.support.id
  name     = "zendesk"
  image    = "ghcr.io/acme/zendesk-mcp:latest"
  command  = "zendesk-mcp --port 8080"
}

# The secret is delivered by reference — its value never enters the state file,
# and it is injected into the tool that needs it, not into the agent.
resource "agyn_env" "zendesk_token" {
  name      = "ZENDESK_TOKEN"
  mcp_id    = agyn_mcp.zendesk.id
  secret_id = agyn_secret.zendesk_token.id
}
terraform init && terraform apply

See the Terraform provider reference for every resource.

How Agyn runs agents

  • Serverless runtime — agents spawn on message, scale to zero on idle. No always-on compute.
  • Any agent container — Claude Code, Codex, or your own. No protocol adaptation required.
  • Environments — one definition pins the runner, compute flavor, images, volumes, and MCP servers every workload gets. Agents and sandboxes both run them.
  • MCP servers in separate containers — each tool gets its own filesystem and process tree. Credentials are injected only into the tool that needs them, never into the agent.
  • Egress rules — the platform attaches credentials to outbound requests at the network edge and denies destinations you have not allowed. The agent calls out with a placeholder; the real token never enters the container.
  • Zero-trust networking — every agent gets its own x509 identity. Deny-by-default access to internal services, including private resources inside your VPC or on-prem network without a bastion.
  • Sandboxes — an engineer launches the same runtime an agent gets, with a shell in the browser, and drives it by hand. Same image, same secrets, same egress rules.
  • Declarative config — define agents and their harness in Terraform. Version-controlled, peer-reviewed, automated.
  • Observability — token usage, compute, tracing, activity logs.

Full architecture: docs/operate/architecture.md.

Video walkthroughs

VideoWhat it shows
Agyn demoAgyn in 3 minutes — From clean cluster to a working agent answering a chat message. End-to-end tour.
Coming soonDeploying agents with Terraform — Define an agent fleet as code, apply it, talk to them.
Coming soonInspecting 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.
  • Local installation — the whole platform in a VM on your machine.
  • Production installation — Helm install, cluster admins, 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:

RepoWhat it is
agynio/platformThis repo. Documentation hub.
agynio/architectureSource-of-truth architecture and product specs.
agynio/bootstrapTerraform stacks for a k3d dev cluster. For a laptop, prefer agyn local.
agynio/platform-chartsProduction Helm charts.
agynio/apiProtobuf schemas for every service.
agynio/terraform-provider-agynTerraform provider.
agynio/agyn-cliPlatform CLI — also what agyn local runs the platform with.
agynio/console-app · chat-app · tracing-app · sandboxes-appBrowser UIs.
agynio/agyn-runtime-codex · agyn-runtime-claude · agyn-runtime-agnAgent runtime images.

Full list with descriptions: docs/reference/service-catalog.md.

Community

Research

Contributing

Good places to start:

License

AGPL-3.0

常见问题

What is platform?

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 228 GitHub stars.

Is platform safe to use?

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.

How do I install platform?

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).

What programming language is platform written in?

platform is primarily written in TypeScript. It is open-source under agynio on GitHub, so you can review or fork the full source.

Are there alternatives to platform?

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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platform — Claude Code AI Skill | SkillTip