pluglayer-mcp 0.26.50615

PlugLayer MCP server — deploy and manage infrastructure via AI

PlugLayer MCP Server

Deploy and manage your infrastructure through natural language with any MCP-compatible AI assistant.

Installation

Option 1: uvx (recommended — no install needed)

PLUGLAYER_API_KEY=your-pluglayer-api-token uvx pluglayer-mcp

This local command mode uses the MCP stdio transport by default, which is the right mode for Cursor, Claude Code, and other editor-launched command servers. The pluglayer-mcp command now always uses stdio so editor clients cannot accidentally switch it into HTTP mode.

Option 2: pip

pip install pluglayer-mcp
PLUGLAYER_API_KEY=your-pluglayer-api-token pluglayer-mcp

Configuration

Claude Desktop

Add to ~/.config/Claude/claude_desktop_config.json:

{
  "mcpServers": {
    "pluglayer": {
      "command": "uvx",
      "type": "stdio",
      "args": ["pluglayer-mcp"],
      "env": {
        "PLUGLAYER_API_KEY": "your-pluglayer-api-token"
      }
    }
  }
}

Cursor

Add to ~/.cursor/mcp.json:

{
  "pluglayer": {
    "command": "uvx",
    "type": "stdio",
    "args": ["pluglayer-mcp"],
    "env": {
      "PLUGLAYER_API_KEY": "your-pluglayer-api-token"
    }
  }
}

Remote HTTP (hosted)

The remote MCP server runs at mcp.pluglayer.com. Pass your token as:

Authorization: Bearer your-pluglayer-api-token

If you intentionally want to run the package itself as an HTTP MCP server, use:

pluglayer-mcp-http

Release Checklist

Before publishing a new pluglayer-mcp build:

1. Confirm local command mode still uses stdio by default.
2. Confirm PLUGLAYER_API_URL override works when pointed at a dev API.
3. Confirm package version will be unique for the publish run.
4. Publish from the public repo main branch after reviewing the dev -> main PR.

After publishing:

1. Restart Cursor, Claude Code, or the MCP client you are testing.
2. If the editor still behaves like an older MCP build, remove and re-add the MCP server entry, then restart the editor.
3. Re-test with a simple command such as:
   • get_current_user
   • list_projects
   • get_compute_summary

Cursor Notes

• For command-based MCP setup, use uvx pluglayer-mcp.
• Do not force HTTP transport for local editor usage.
• pluglayer-mcp always uses stdio, which is the correct transport for Cursor-launched command servers.
• Only use pluglayer-mcp-http when you intentionally want to run the package itself as an HTTP MCP server.

Available Tools

The MCP calls the PlugLayer FastAPI backend instead of re-implementing backend business logic. Auth, roles, ownership, compute guards, and k3s orchestration remain in the backend. MCP and editor plugins should authenticate with a PlugLayer API token created in the PlugLayer Settings page, not the browser/session auth token.

Managed registries are configured by PlugLayer admins in the platform UI/API. When deploy_image uses mirroring, the backend picks a registry the current user is allowed to use and keeps Kubernetes pull secrets in sync automatically.

Tool	Description
get_current_user	Show the Authentik-backed user and roles
list_projects	List authenticated user's projects
get_my_projects	Alias for listing the current user's projects
create_project	Create a new project namespace
get_project	Get project details, current apps in the project, and attached custom-domain state
get_compute_summary	Show account-level personal + shared compute capacity; estimate first when sizing is still unclear
get_my_available_compute	Show the current user's available compute capacity; pair with estimate first for planning
get_my_available_computes	Alias for available compute capacity
estimate_compute	Estimate required compute, monthly price, and a tailored offer link; preferred before purchase/allocation decisions
list_nodes	List accessible compute nodes
add_node_ssh	Add a personal SSH node usable by all of the user's projects
list_registries	List the registries currently available to the user
deploy_image	Mirror a Docker image into PlugLayer's managed Docker Hub namespace, then deploy it after backend compute checks
deploy_compose	Deploy from docker-compose.yml after backend compute checks
list_deployments	List running apps/deployments
get_apps_by_project	List apps inside a specific project; use this before deploy when you need to clarify update vs replace vs separate new app
get_deployment_status	Check app status and URL
get_logs	Get app logs
get_app_logs	Alias for getting app logs
redeploy	Redeploy an app
restart_app	Alias for restarting an app by redeploying it
rollback	Roll back to previous version
delete_deployment	Delete an app
list_project_domains	List custom domains for a project
get_domains_by_project	Alias for project-domain lookup; use this before asking which domain the user wants so existing project domains can be offered as options
add_custom_domain	Add a single or wildcard custom domain and return DNS records
verify_custom_domain	Verify TXT/CNAME DNS and activate if attached
attach_custom_domain	Attach a verified custom domain to an app
detach_custom_domain	Detach a domain while keeping verification
remove_custom_domain	Remove a domain and its route
get_task_status	Poll async operation progress
generate_github_actions	Get CI/CD pipeline YAML
get_cluster_health	Check cluster status

Example Conversations

Deploy your first app:

"I have a FastAPI app at ghcr.io/myorg/api:latest that runs on port 8000. Deploy it to my production project."

Convert docker-compose:

"Here's my docker-compose.yml: [paste]. Deploy this to PlugLayer."

Add a node:

"Add my server at 192.168.1.100 as personal compute. Here's my SSH key: [paste]"

CI/CD setup:

"Generate a GitHub Actions workflow for my api deployment so it auto-deploys on push to main."

Add a custom domain:

"Add api.example.com to my production project, show me the DNS records, then verify it and attach it to my API app."

Getting Your API Key

1. Go to PlugLayer Settings
2. Create a PlugLayer API token
3. Copy it once and store it safely
4. Use it as PLUGLAYER_API_KEY for MCP, editor plugins, and CI/CD webhook deploys