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AI skill

Let AI deploy projects with Appaloft.

After the Appaloft skill is installed, AI can inspect a project, call the Appaloft CLI/API/Web deployment path, and return URLs, logs, diagnostics, and recovery commands. The MCP/tool gateway connects tool calls, permissions, and audit.

Entrypoint

AI agent

State owner

CLI / API / Web

MCP

public tools + Cloud gateway

Secrets

Reference, never print

Outcome

URL + logs + diagnostics

The install command only installs the skill
Inspect source and project shape before deploy
MCP tools call existing Appaloft deployment capabilities
Return live URL, logs, diagnostics, and recovery commands

Deployment request

The skill recognizes deploy, status, recovery, and configuration requests, then calls existing CLI, API, or Web capabilities.

MCP tool layer

The MCP/tool gateway connects AI tool calls to Appaloft. In hosted Cloud, it also adds sign-in, permissions, policy, and audit.

Safety boundary

AI must avoid .env files, private keys, tokens, cookies, and unmasked secrets. When credentials are needed, it should reference Appaloft secrets, GitHub Secrets, or runtime environment variable names.

Result packet

A normal response includes the URL, deployment id, resource id, status, logs, diagnostics, and recovery guidance.

Deployment flow

1

Install

Install the Appaloft skill into a skill-capable AI host.

2

Ask AI

Ask the agent to deploy the current repository and return URL, logs, diagnostics, and recovery commands.

3

Verify

On failure, read structured status and recovery guidance before choosing the next step.

Related topics

Keep following the same deploy path.

Appaloft SEO pages are organized around real deployment tasks. Each page should lead to the next useful step, not stand alone.