Control Plane AI Plugin
MCP serverCloud & infraControl Plane is a cloud platform for deploying and operating workloads. Once this integration is added, your AI can deploy and manage workloads across AWS, GCP, Azure, and other cloud providers, so cloud work can be handled directly in your conversation.
Use Control Plane AI Plugin in Claude, ChatGPT or Ahel Desktop
Free. Sign in, add Control Plane AI Plugin and connect your AI. About a minute.
Also: Claude Code · Cursor · Codex
Then ask your AI: use Control Plane AI Plugin
Needs your own Control Plane AI Plugin account. You sign in to it and approve access when you connect.
Details
Available today. Use it from your connected AI after setup.
After adding the integration, tell your AI what you want to deploy and which cloud it should run on. From there, you can ask it to help operate those workloads whenever needed.
What your AI can do with it
- Deploy workloads to AWS, GCP, Azure, and other cloud providers
- Operate workloads running across multiple clouds
- Manage deployments on different clouds from one place
- Handle AWS, GCP, and Azure workloads without switching between tools
Install Control Plane AI Plugin
The server’s own address, for the clients that take one directly. Or connect Ahel once and every client you use reads it from one address, with the account kept on Ahel rather than in each client’s config.
Claude Code
claude mcp add --transport http --scope user control-plane-ai-plugin 'https://mcp.cpln.io/mcp'Run it once in your project, then open /mcp to approve any sign-in the server asks for.
Claude Desktop
https://mcp.cpln.io/mcpAdd a custom connector in Settings, paste this address, and approve the sign-in.
Cursor
cursor://anysphere.cursor-deeplink/mcp/install?name=control-plane-ai-plugin&config=eyJ1cmwiOiJodHRwczovL21jcC5jcGxuLmlvL21jcCJ9Open the link and Cursor adds the server at that address.
ChatGPT
https://mcp.cpln.io/mcpIn Settings, enable Developer mode, create an MCP app, and paste this address. Your plan and workspace must allow custom apps.
Codex
codex mcp add control-plane-ai-plugin --url 'https://mcp.cpln.io/mcp'Run it once, then sign in with codex mcp login control-plane-ai-plugin if the server asks for an account.
From the project's README
As published by controlplane-com/ai-plugin in README.md.
Run containerized workloads across AWS, GCP, Azure, OCI, and your own hardware under one API. It loads Control Plane's domain knowledge, production guardrails, and live MCP tools into Claude Code, Codex, and Antigravity CLI so your assistant can deploy, troubleshoot, secure, and migrate workloads with verified cpln commands.
Installation
Claude Code
/plugin marketplace add https://github.com/controlplane-com/ai-plugin.git
/plugin install cpln@controlplane
/reload-plugins
Update with /plugin marketplace update controlplane then /reload-plugins (third-party marketplaces don't auto-update unless you enable it in /plugin → Marketplaces).
Alternatively, install from Anthropic's community plugin marketplace, where every listing has passed Anthropic's review:
/plugin marketplace add anthropics/claude-plugins-community
/plugin install cpln@claude-community
/reload-plugins
Codex
codex plugin marketplace add https://github.com/controlplane-com/ai-plugin.git
Start Codex, open /plugins, and install cpln. The MCP handshake supplies the core rules. Local installations also include optional session hooks, which must be reviewed and trusted in Codex before they run.
Update with codex plugin marketplace upgrade controlplane, then restart Codex.
Antigravity CLI
Install the plugin with Antigravity CLI (agy):
agy plugin install https://github.com/controlplane-com/ai-plugin/plugins/cpln
Generic MCP client
Point any other MCP client at the hosted server:
{
"mcpServers": {
"cpln": {
"type": "http",
"url": "https://mcp.cpln.io/mcp"
}
}
}
The bare URL serves the default core tool set. A client that loads tools on demand can add ?toolsets=full for every tool.
Authentication
MCP uses OAuth 2.1 + PKCE. Sign in to let the assistant act on your Control Plane organizations — you choose which orgs it may operate on, and the token is scoped to those orgs and enforced server-side on every call. Sign in again to change the grant. Treat MCP access as production access to the orgs you grant. How to sign in:
- Claude Code —
/mcp, selectcpln, sign in (orclaude mcp login cpln). - Codex —
codex mcp login cpln. - Antigravity CLI —
/mcp, selectcpln, authenticate.
Environment variables
Optional — only for the cpln CLI workflows some skills generate (CI/CD, Terraform, Pulumi). See .env.example.
| Variable | Purpose |
|---|---|
CPLN_TOKEN | Service-account token for cpln CLI calls (sensitive). |
CPLN_ORG | Default organization. |
CPLN_GVC | Default GVC. |
CPLN_PROFILE | Local cpln CLI profile. |
Usage
Ask in natural language — the assistant routes to the right skill or agent:
- "Troubleshoot why my
payments-apiworkload inproductionkeeps restarting." - "Put
app.example.comin front of mywebworkload with auto-TLS." - "Give my
analyticsworkload credential-free read access to S3 bucketprod-event-logs— no IAM keys." - "Provision a production Postgres with HA failover and S3 backups."
- "Convert this
kustomization.yamlto Control Plane and apply it tostagingafter I confirm."
Two workflows also have slash commands in Claude Code — /cpln:troubleshoot WORKLOAD and /cpln:migrate-k8s FILE; in other clients, ask for the same workflows by name.
What's included
- Domain skills across CLI usage, access control, autoscaling, networking, observability, migration, templates, stateful storage, and security.
- Two guided agents: workload troubleshooting and Kubernetes / Compose / Helm migration.
- A short always-on rule set the assistant applies in every session, with the full operating guide read on demand.
- Pre-configured access to the hosted Control Plane MCP server.
Security
- MCP access is production access — scoped to the orgs you grant and your own RBAC.
- Destructive actions (deleting resources, shrinking/deleting volumes, replacing workloads, applying to production) require explicit confirmation.
- Secret values never pass through the chat: Control Plane generates the values nobody needs to know, the user types their own values into the Console, and tools return secret metadata only.
- The plugin stores no logs, secrets, prompts, or telemetry; your AI client and model provider process prompts per their own policies.
Report vulnerabilities per SECURITY.md.
Where data goes
The plugin's one declared connector is the hosted MCP server at https://mcp.cpln.io/mcp, which acts only on the orgs you grant when you sign in, with your own permissions.
When a task needs it, the skills also run these tools on your machine, each with your own credentials:
| Tool | Sends data to |
|---|---|
cpln CLI | The Control Plane API (api.cpln.io), your org's image registry (ORG.registry.cpln.io), and the metrics endpoint (metrics.cpln.io), using your CLI profile or CPLN_TOKEN |
docker | The image registries you push to and pull from |
kubectl, helm | The Kubernetes cluster you point them at, when migrating from it or installing the Control Plane Kubernetes operator |
terraform, pulumi | The Control Plane API, through the Control Plane provider |
gcloud and other cloud CLIs | Your own cloud account, when connecting a private network or creating an agent VM |
curl | Your own domain, to check it after setup |
The plugin itself stores nothing. Resources, app files, and invitations the assistant creates are stored in your Control Plane org until you delete them, and the org's audit trail records each change.
More
- Contributing: CONTRIBUTING.md
- Docs: docs.controlplane.com · Support:
support@controlplane.comor Slack - License: MIT — see LICENSE
Signals
- GitHub stars
- 10
- Forks
- 1
- Last commit
- Sep 2026
Advanced
- Delivery
- control-plane MCP server → your Ahel connector (mcp.ahel.ai) → your AI.
- Item type
- mcp-server
- Key
io-cpln-control-plane- Source
- github.com/controlplane-com/ai-plugin
- Hosted endpoint
https://mcp.cpln.io/mcp
github.com/controlplane-com/ai-plugin
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