# InsideOut

> Use this tool when you need to design and deploy cloud infrastructure on AWS or GCP without requiring extensive technical expertise. InsideOut solves the problem of manually configuring and provisioning cloud resources by generating production-ready Terraform code and estimating monthly costs based on plain English application descriptions. It takes in natural language inputs and outputs modular Terraform configurations, cost estimates, and provisions infrastructure with live monitoring and drift detection.

Canonical page: https://skillsregistry.net/skills/luther-systems-insideout  
JSON: https://api.skillsregistry.net/v1/skills/luther-systems-insideout

## Description

Conversational AI agent that designs AWS or GCP infrastructure end-to-end — describe your application in plain English, and Riley designs the architecture, generates production-ready Terraform, estimates monthly costs, and deploys.

## Highlights

- **24 tools** across design, deployment, and post-deploy infrastructure inspection
- Coverage of 50+ AWS and GCP services
- Module-by-module Terraform output (networking, compute, storage, auth, observability, …)
- Cost estimates broken down per component before any deploy
- One-command provisioning to AWS or GCP, then live monitoring + drift detection
- No Terraform expertise required

## Hosted

Streamable HTTP, no-auth required: `https://app.luthersystems.com/v1/insideout-mcp`

## Other listings

- **mcp.so:** https://mcp.so/server/insideout
- **Glama:** https://glama.ai/mcp/servers/luthersystems/insideout-agent-skills
- **Official MCP Registry:** `com.luthersystems.insideout/mcp`

## Source

Skills bundle and MCP discovery artifacts: https://github.com/luthersystems/insideout-agent-skills

## Trust

- **Trust score (0–1):** 0.30
- **Verification tier:** unverified
- **Last scanned:** 2026-08-30

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** version-control
- **Updated:** 2026-08-30

## Source

- **Source listing:** [Smithery](https://smithery.ai/server/luther-systems/insideout)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "luther-systems-insideout"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/luther-systems-insideout` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/luther-systems-insideout/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt