Design, price, and deploy production-ready AWS & GCP infrastructure through conversational AI
Kiro Power • InsideOut • Luther Systems
InsideOut is a Kiro IDE power that brings AI-powered cloud infrastructure design directly into your editor. Describe what you want to build in plain language, and Riley — your AI infrastructure advisor — guides you through selecting services, configuring them, estimating costs, generating Terraform, and deploying to AWS or GCP.
No authentication or API keys required. Install the power and start designing.
- Design infrastructure conversationally — describe your app, get expert recommendations
- Get real-time cost estimates — see monthly costs as components are added
- Generate Terraform — production-ready, modular code with security best practices
- Deploy with one command — deploy directly to AWS or GCP from the conversation
- Inspect deployments — verify what was actually provisioned in your cloud account
- Compare providers — evaluate AWS vs GCP options side-by-side
| AWS | GCP |
|---|---|
| ECS, EKS, Lambda, Fargate | Cloud Run, GKE, Cloud Functions |
| RDS, DynamoDB, ElastiCache | Cloud SQL, Firestore, Memorystore |
| ALB, CloudFront, Route 53 | Cloud Load Balancing, Cloud CDN |
| S3, EFS | Cloud Storage, Filestore |
| VPC, Security Groups | VPC, Firewall Rules |
| CloudWatch, SNS, SQS | Cloud Monitoring, Pub/Sub |
| And 15+ more | And 10+ more |
- Open Kiro IDE
- Open the Powers panel
- Click Add power from GitHub
- Enter:
luthersystems/insideout-power
- Clone this repo:
git clone https://github.com/luthersystems/insideout-power.git - Open Kiro IDE
- Open the Powers panel
- Click Add power from Local Path
- Select the cloned directory
MCP support must be enabled in Kiro:
- Open Settings (
Cmd + ,/Ctrl + ,) - Search for "MCP"
- Enable the MCP support setting
That's it. No API keys, no local binaries, no additional setup.
Once installed, mention anything about infrastructure, cloud, AWS, GCP, Terraform, or deployment in a Kiro chat. The power activates automatically.
You: "I need to set up cloud infrastructure for a web app"
Kiro: [Activates InsideOut power, calls convoopen]
Riley: "Hi! I'm Riley, your infrastructure advisor. Tell me about the app
you're building — what does it do, who uses it, and what scale
are you planning for?"
You: "It's an e-commerce platform expecting 50k monthly users on AWS"
Riley: "Great! I'd recommend ECS Fargate for your containers, RDS PostgreSQL
for your database, ElastiCache Redis for sessions, and an ALB.
Estimated cost: ~$350/month. Want me to adjust anything?"
You: "Looks good, generate the Terraform"
Kiro: [Calls tfgenerate — downloads production-ready Terraform files]
You: "Deploy it"
Kiro: [Calls tfdeploy — deploys to AWS, streams logs via tflogs]
| Tool | Description |
|---|---|
convoopen |
Start a new infrastructure design session |
convoreply |
Continue the design conversation with Riley |
convoawait |
Wait for long-running operations |
convostatus |
View current components, config, and pricing |
tfgenerate |
Generate production-ready Terraform files |
tfdeploy |
Deploy generated Terraform to AWS or GCP |
tfstatus |
Check deployment progress |
tflogs |
Stream real-time deployment logs |
awsinspect |
Inspect deployed AWS resources |
gcpinspect |
Inspect deployed GCP resources |
help |
Get workflow guidance |
insideout-power/
├── POWER.md # Power metadata, onboarding, and agent instructions
├── mcp.json # MCP server configuration (remote HTTP)
├── README.md # This file
├── LICENSE # Apache 2.0
├── assets/
│ ├── banner.svg # GitHub banner
│ └── logo.svg # InsideOut logo
└── steering/ # Workflow-specific guidance for the agent
├── getting-started.md # First-time setup walkthrough
├── aws-design-patterns.md # AWS architecture patterns and prompts
├── gcp-design-patterns.md # GCP architecture patterns and prompts
└── troubleshooting-guide.md
InsideOut uses a multi-agent AI system behind a single MCP server:
| Agent | Role |
|---|---|
| Riley | Infrastructure advisor — leads the design conversation |
| Hippo | Cost estimation and pricing optimization |
| Joy | User experience and requirement gathering |
| Etch | Terraform code generation |
| Core | Architecture validation and best practices |
| Axel | Deployment orchestration |
The conversation flows through these agents automatically. From Kiro's perspective, you're talking to Riley — the other agents work behind the scenes.
- Fork this repository
- Create a feature branch:
git checkout -b feature/my-improvement - Make your changes
- Test locally: Install the power from local path in Kiro
- Submit a pull request
- Test POWER.md changes by reinstalling the power from local path
- Verify MCP connectivity with the
helptool after changes - Steering files are loaded on-demand — test each workflow independently