Mcloud Environments logo

Mcloud Environments

Organization
medusajs
mcloud-environments

Execute mcloud environments commands to list, get, create, delete, redeploy, or trigger builds for Cloud environments. Use when managing environment lifecycle, redeploying after variable changes, or starting new builds from source.

Overview

Publishermedusajs
Repositorymedusa-agent-skills
Skill namemcloud-environments
Stars
218
Forks
27
Bundled files
Instructions only
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by medusajs on GitHub. Read the source before you install it.

Installation

Install the Mcloud Environments AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/medusajs/medusa-agent-skills.git /tmp/medusa-agent-skills
mkdir -p .claude/skills
cp -r /tmp/medusa-agent-skills/plugins/medusa-cloud/skills/mcloud-environments .claude/skills/mcloud-environments
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Mcloud Environments in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Mcloud Environments on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Mcloud Environments is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Cloud CLI: Environments Commands

Execute mcloud environments commands to manage environment lifecycle and deployments.

Constraints

  • Production environments cannot be deleted. Always check type via environments get --json before attempting delete in automation.
  • Use --yes for destructive operations (delete) in non-interactive contexts.
  • redeploy vs trigger-build are not interchangeable — choose the right one based on where the fix is.

Commands

environments list

List all environments in a project.

bash
mcloud environments list --organization <org-id> --project <project-id-or-handle> --json

Options:

  • -o/--organization <id> — Organization ID (falls back to active context)
  • -p/--project <id-or-handle> — Project ID or handle (falls back to active context)
  • --json — Output as JSON

environments get

Retrieve a single environment by its ID or handle.

bash
mcloud environments get <environment-id-or-handle> --organization <org-id> --project <project-id-or-handle> --json

Arguments:

  • environment — Environment ID or handle (required)

Options:

  • -o/--organization <id>, -p/--project <id-or-handle>, --json

environments create

Create a new long-lived environment.

bash
mcloud environments create \
  --organization <org-id> \
  --project <project-id-or-handle> \
  --name "Staging" \
  --branch develop \
  --json

Options:

  • -o/--organization <id>, -p/--project <id-or-handle>
  • -n/--name <name> — Environment name (required)
  • -b/--branch <branch> — Git branch to track (required)
  • --custom-subdomain <subdomain> — Optional custom subdomain
  • --json — Output as JSON

environments delete

Delete an environment. Cannot delete production environments.

bash
mcloud environments delete <environment-id-or-handle> \
  --organization <org-id> \
  --project <project-id-or-handle> \
  --yes

Arguments:

  • environment — Environment ID or handle (required)

Options:

  • -o/--organization <id>, -p/--project <id-or-handle>
  • -y/--yes — Skip confirmation prompt (required in non-interactive mode)
  • --json — Output as JSON

environments redeploy

Re-run an existing build for the active deployment. Use when the fix is environment-side (variable change, infra issue) — does NOT start a new build.

bash
mcloud environments redeploy <environment-id-or-handle> \
  --organization <org-id> \
  --project <project-id-or-handle> \
  --json

Arguments:

  • environment — Environment ID or handle (required)

Options:

  • -o/--organization <id>, -p/--project <id-or-handle>, --json

Requires the environment to have an active deployment. If it doesn't, use trigger-build first.

environments trigger-build

Start a new build from the tracked branch. Use when the fix is committed code — creates a new deployment.

bash
mcloud environments trigger-build <environment-id-or-handle> \
  --organization <org-id> \
  --project <project-id-or-handle> \
  --json

Arguments:

  • environment — Environment ID or handle (required)

Options:

  • -o/--organization <id>, -p/--project <id-or-handle>, --json

Redeploy vs Trigger-Build Decision

CommandWhen to use
redeployFix is environment-side (variable change, infra config) — reruns existing build
trigger-buildFix is in source code on the tracked branch — starts a new build

Examples

bash
# List all environments
mcloud environments list --json

# Get environment details and check type before deleting
mcloud environments get staging --json | jq '{id, name, type, status}'

# Create a new environment tracking the develop branch
mcloud environments create --name "Staging" --branch develop --json

# Delete a non-production environment
mcloud environments delete staging --yes

# Redeploy after a variable change
mcloud environments redeploy production --json

# Trigger a fresh build from source
mcloud environments trigger-build production --json

# Find environment handles by name
mcloud environments list --json \
  | jq -r '.[] | select(.name == "Production") | .handle'

# Verify new build started
mcloud deployments list --environment production --limit 5 --json \
  | jq '.[] | {id, backend_status, updated_at}'

Frequently asked questions

What does the Mcloud Environments AI skill do?

Execute mcloud environments commands to list, get, create, delete, redeploy, or trigger builds for Cloud environments. Use when managing environment lifecycle, redeploying after variable changes, or starting new builds from source.

Why use Mcloud Environments on TypingMind?

Because you install it once and use it with any model. Mcloud Environments is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Mcloud Environments in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/medusajs/medusa-agent-skills/tree/main/plugins/medusa-cloud/skills/mcloud-environments. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Mcloud Environments?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Mcloud Environments?

As many as you like. As long as a model supports skills, you can use Mcloud Environments with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Mcloud Environments AI skill free?

It is published on GitHub by medusajs. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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