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PlugLayer MCP server — deploy and manage infrastructure via AI

Project description

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.

Databases are a first-class Data Layer workflow in MCP. When a user needs a new database, wants to know whether one already exists, asks for a connection string, or needs env vars to wire an app to a database, the preferred MCP path is:

  1. list_user_databases
  2. if needed, list_database_templates
  3. check_slug_availability
  4. optionally check_database_slug_availability
  5. create_database
    • the MCP tool resolves required deploy-time database env vars itself
    • password/secret/token/key fields are generated there when the template expects a random value
    • database-name placeholders are filled from the chosen app name
  6. get_task_status
  7. get_database_connection_details
  8. optionally get_database_logs when troubleshooting
  9. use update_database_access, restart_database, or remove_database for follow-up lifecycle actions

After provisioning a database, the assistant should proactively suggest or apply exact env var updates for dependent apps instead of leaving the user with only a raw connection string.

Marketplace template deployment through MCP now supports both:

  1. deploying into an existing project by project_id
  2. creating a new project inline by passing project_name
Tool Description
get_current_user Show the Authentik-backed user and roles
get_user_context Load the caller's stored user memory/context
update_user_context Update the caller's stored user memory/context
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
remove_project Remove one of the user's projects by deleting its apps first, requesting namespace cleanup, and then archiving the project record/history
delete_project Alias for remove_project
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
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; if a similar app already exists and the namespace is full, use update/replace flow instead of a brand-new app
upload_image_archive_and_deploy Upload a locally built image archive from the user's machine, push it into an allowed registry, and deploy it
upload_image_archive_and_redeploy_app Upload a newly rebuilt image archive for an existing app, push it with a new tag, keep the slug unchanged, and redeploy that app
deploy_compose Analyze docker-compose.yml, split it into separate deploy units, route known databases through Data Layer templates, deploy remaining services as separate apps, and require uploaded archives for local-build services
analyze_compose_deploy_plan Preview how PlugLayer will split a docker-compose stack into Data Layer databases, separate compose apps, and local-build image services
get_compose_local_build_commands Generate exact docker buildx, smoke-test, and OCI export commands for local-build compose services before they are uploaded and deployed
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, especially when a full namespace should block duplicate new-app deploys
check_slug_availability Check whether a PlugLayer slug is free inside a project before deploy or rename
get_deployment_status Check app status and URL
get_logs Get app logs
get_app_logs Alias for getting app logs
get_app_connection_env_vars Get concrete connection env vars and connection strings for an app/database so dependent apps can be updated correctly
list_marketplace_templates List deployable marketplace templates before choosing one for a project
get_marketplace_template Inspect one marketplace template, including its required env vars
deploy_marketplace_template Deploy a marketplace template into an existing project or create a new project inline during the same MCP flow
exec_app_terminal Execute a command in the caller's own deployed app container
redeploy Redeploy an app after confirming the exact app name; the existing slug stays unchanged
restart_app Alias for restarting an app by redeploying it
rollback Roll back to previous version
remove_app Remove one of the user's apps, tear down its runtime workload, revoke active routing, and mark it as removed
delete_app Alias for remove_app
delete_deployment Alias for remove_app
list_database_templates List ready-to-deploy database templates
list_user_databases List the caller's provisioned databases, optionally by project
check_database_slug_availability Check whether a Data Layer slug is free in a project before provisioning or renaming a database
create_database Provision a database from a template after backend compute and project checks, resolving password-like env vars inside the MCP flow first
get_database_connection_details Get connection strings, env vars, and docs for a provisioned database
sync_database_env_to_app Patch one app's env vars from a provisioned database's concrete connection fields, then restart the existing app
get_database_logs Read logs from a provisioned database app
update_database_access Update the public TCP IP allowlist for a provisioned database
restart_database Restart a provisioned database by queueing its restart flow
remove_database Remove a provisioned database and tear down its runtime workload/routing
delete_database Alias for remove_database
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
detect_custom_domain_provider Detect the likely DNS/domain provider so the user can confirm it before DNS instructions are shown
add_custom_domain Add a single or wildcard custom domain and return DNS records in a provider-friendly table
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
get_task_status Poll async operation progress
inspect_local_github_repo Check whether the local repo has git plus a GitHub origin configured
generate_github_actions Get GitHub Actions YAML for a 3-step PlugLayer CI/CD flow: build OCI image, upload it to the same app id, then merge env vars and restart/redeploy

Example Conversations

Deploy your first app:

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

Convert docker-compose:

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

CI/CD setup:

"Generate a GitHub Actions workflow for my api app so every push rebuilds it, uploads it to PlugLayer, and redeploys the same app id."

The generated workflow expects:

  • public reusable actions from pluglayer/actions
  • required secrets:
    • PLUGLAYER_API_KEY
  • optional secrets:
    • PLUGLAYER_API_URL (defaults to https://api.pluglayer.com)
    • PLUGLAYER_BUILD_ENV_JSON (JSON object of build-time env vars/build args to inject during image build)

Add a custom domain:

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

Provision a database and wire the backend to it:

"Create a Postgres database in my marketplace project, check whether the slug postgres is available first, and after it finishes show me the connection env vars so we can update my backend."

Reuse an existing database instead of creating a new one:

"Check whether I already have a Mongo or Postgres database in my project. If I do, show me the connection details and suggest the backend env vars I should update."

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 the 3-step CI/CD actions flow

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