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A intelligent CLI tool that analyzes your project and deploys it to AWS, GCP, or Azure with human-in-the-loop validation.

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Agent Cloud

AI-Powered Multi-Cloud Deployment Platform

Deploy your applications to AWS, GCP, or Azure with intelligent AI agents that analyze your project, generate deployment plans, and execute real cloud deployments—all from a single CLI.

TypeScript Node.js License

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Features

AI-Powered Intelligence

  • Smart Project Analysis - Automatically detects your tech stack and dependencies
  • Intelligent Planning - AI generates optimal deployment strategies
  • Environment Validation - Validates cloud credentials and configurations

Multi-Cloud Support

Deploy to 3 major cloud providers with 13 deployment targets:

Cloud Container Serverless Static Sites PaaS
AWS ECS Fargate Lambda S3 -
GCP Cloud Run Cloud Functions Firebase + Storage App Engine
Azure Container Apps Functions Static Web Apps + Blob App Service

Production-Ready

  • Comprehensive Logging - Session-based logs with 5 levels
  • Error Handling - Friendly messages with recovery suggestions
  • Deployment History - Complete audit trail with analytics
  • Cost Tracking - Estimated costs per deployment
  • Performance Monitoring - Duration and success rate tracking

Intelligent Workflows

  • Human-in-the-Loop - Approval gates before deployment
  • Suspend/Resume - Review plans before proceeding
  • Multi-Step Orchestration - Automated multi-phase deployments

Prerequisites

Before using Agent Cloud, ensure you have:

Required

Cloud Provider CLIs (for the clouds you want to use)

  • AWS CLI - For AWS deployments (Install)
  • gcloud CLI - For GCP deployments (Install)
  • Azure CLI - For Azure deployments (Install)

API Keys (Choose one or both)

  • OpenAI API Key - For AI agents (Get Key)
  • Google Gemini API Key - Alternative AI provider (Get Key)

Quick Start

1. Installation

# Clone the repository
git clone https://github.com/intojhanurag/agent-cloud.git
cd agent-cloud

# Install dependencies
pnpm install

# Build the project
pnpm build

# Make CLI globally available
pnpm link --global

2. Configure Cloud Provider

Choose your cloud provider and authenticate:

For AWS:

aws configure
# Enter your AWS Access Key ID, Secret Access Key, and region

For GCP:

gcloud auth login
gcloud config set project YOUR_PROJECT_ID

For Azure:

az login
az account set --subscription YOUR_SUBSCRIPTION_ID

3. Set Environment Variables

Create a .env file in the project root:

# AI Provider (Choose one)
OPENAI_API_KEY=your_openai_api_key_here
# OR use Google Gemini
GOOGLE_GENERATIVE_AI_API_KEY=your_gemini_api_key_here

# Optional - Cloud configurations
AWS_REGION=us-east-1
GCLOUD_PROJECT=your-gcp-project
GCLOUD_REGION=us-central1
AZURE_RESOURCE_GROUP=agent-cloud-rg
AZURE_LOCATION=eastus

4. Your First Deployment

# Navigate to your project directory
cd /path/to/your/project

# Deploy to AWS (interactive mode)
cloud-agent deploy --cloud aws

# Review the deployment plan
# Approve when ready

# OR: Deploy with auto-approval
cloud-agent deploy --cloud aws --yes

That's it! Your application is now deployed to the cloud!

Usage Guide

Available Commands

# Deploy to cloud
cloud-agent deploy --cloud <aws|gcp|azure> [--yes]

# View deployment status
cloud-agent status

# List workflow history
cloud-agent workflows

# View help
cloud-agent --help

Deployment Flow

When you run cloud-agent deploy, here's what happens:

Phase 1: Environment Validation
  - Validates cloud credentials
  - Checks CLI installation
  - Verifies network connectivity

Phase 2: Project Analysis
  - Detects project type (static, API, container)
  - Identifies runtime and framework
  - Analyzes dependencies

Phase 3: Deployment Planning
  - Generates cloud-specific plan
  - Estimates costs
  - Prepares deployment commands

Phase 4: Human Approval
  - Shows deployment plan
  - Waits for confirmation
  - (Skip with --yes flag)

Phase 5: Cloud Deployment
  - Authenticates with cloud provider
  - Creates cloud resources
  - Deploys your application
  - Returns deployment URL

Cloud-Specific Guides

AWS Deployments

Static Sites - S3

# Build your static site
npm run build

# Deploy to AWS S3
cloud-agent deploy --cloud aws --yes

APIs/Containers - ECS Fargate

# Deploy Node.js API
cloud-agent deploy --cloud aws --yes

# Your app will be containerized and deployed to ECS

Required AWS Permissions:

  • ECS (Fargate)
  • EC2 (VPC, Security Groups)
  • S3 (for static sites)
  • IAM (for service roles)

GCP Deployments

Static Sites - Firebase Hosting

# Deploy to Firebase (best static hosting)
cloud-agent deploy --cloud gcp --yes

APIs/Containers - Cloud Run

# Deploy to Cloud Run (simplest container platform)
cloud-agent deploy --cloud gcp --yes

Required GCP APIs:

  • Cloud Run API
  • Cloud Build API
  • Firebase Hosting API (for static sites)
  • Cloud Storage API

Azure Deployments

Static Sites - Static Web Apps

# Deploy to Azure Static Web Apps (with global CDN)
cloud-agent deploy --cloud azure --yes

APIs/Containers - Container Apps

# Deploy to Azure Container Apps
cloud-agent deploy --cloud azure --yes

Required Azure Services:

  • Container Apps
  • Container Registry
  • Static Web Apps (for static sites)
  • Resource Groups

Deployment History & Analytics

Agent Cloud automatically tracks all deployments with detailed analytics.

View Deployment History

# View logs from last deployment
cat .agent-cloud/logs/deployment-*.log

# View deployment history
cat .agent-cloud/config.json

Configuration File

Your deployment history is stored in .agent-cloud/config.json:

{
  "version": "1.0.0",
  "projectName": "my-app",
  "defaultCloud": "aws",
  "deployments": [
    {
      "id": "1737363780000",
      "timestamp": "2026-01-20T12:23:00.000Z",
      "cloud": "aws",
      "projectPath": "./",
      "success": true,
      "deploymentUrl": "https://my-app.aws.com",
      "resources": {
        "cluster": "my-cluster",
        "service": "my-service"
      },
      "cost": 45.00,
      "duration": 142500
    }
  ],
  "preferences": {
    "logLevel": "info",
    "region": {
      "aws": "us-east-1",
      "gcp": "us-central1",
      "azure": "eastus"
    }
  }
}

Analytics

View deployment statistics programmatically:

import { getConfigManager } from './src/utils/config.js';

const config = getConfigManager();
const stats = config.getStats();

console.log('Total Deployments:', stats.total);
console.log('Success Rate:', (stats.successful / stats.total * 100).toFixed(1) + '%');
console.log('Total Cost:', '$' + stats.totalCost.toFixed(2) + '/month');
console.log('Average Duration:', (stats.averageDuration / 1000).toFixed(1) + 's');

Examples

📦 Complete Demo Application

Want to see a full working example? Check out our Simple Node.js API Demo!

This complete example includes:

  • ✅ Full REST API with CRUD operations
  • ✅ Docker configuration for all cloud providers
  • ✅ Comprehensive deployment instructions
  • ✅ API testing scripts
  • ✅ Step-by-step deployment guide

Quick start:

cd examples/simple-nodejs-api
npm install
npm start

# Then deploy to any cloud:
cloud-agent deploy --cloud aws

👉 Read the full example README →

Example 1: Deploy React App to AWS

# In your React project
cd my-react-app

# Build the production bundle
npm run build

# Deploy to AWS S3
cloud-agent deploy --cloud aws --yes

# Output:
# Deployment to AWS completed successfully!
# URL: https://my-react-app.s3-website-us-east-1.amazonaws.com
# Duration: 45.2s
# Estimated Cost: $3.00/month

Example 2: Deploy Node.js API to GCP

# In your Node.js API project
cd my-node-api

# Deploy to Cloud Run
cloud-agent deploy --cloud gcp --yes

# Output:
# Deployment to GCP completed successfully!
# URL: https://my-node-api-abc123.run.app
# Duration: 127.8s
# Estimated Cost: $25.00/month

Example 3: Deploy Next.js App to Azure

# In your Next.js project
cd my-nextjs-app

# Build the app
npm run build

# Deploy to Azure Static Web Apps
cloud-agent deploy --cloud azure --yes

# Output:
# Deployment to Azure completed successfully!
# URL: https://my-nextjs-app.azurestaticapps.net
# Duration: 98.5s
# Estimated Cost: $0.00/month (Free tier)

Configuration Options

Environment Variables

# AI Configuration (Choose one)
OPENAI_API_KEY=sk-...                    # Option 1: OpenAI API key
GOOGLE_GENERATIVE_AI_API_KEY=...         # Option 2: Google Gemini API key

# AWS Configuration
AWS_REGION=us-east-1                     # Default: us-east-1
AWS_ACCESS_KEY_ID=AKIA...                # Optional: AWS credentials
AWS_SECRET_ACCESS_KEY=...                # Optional: AWS credentials

# GCP Configuration
GCLOUD_PROJECT=my-project                # Required for GCP
GCLOUD_REGION=us-central1                # Default: us-central1
GOOGLE_CLOUD_PROJECT=my-project          # Alternative to GCLOUD_PROJECT

# Azure Configuration
AZURE_SUBSCRIPTION_ID=...                # Required for Azure
AZURE_RESOURCE_GROUP=agent-cloud-rg      # Default: agent-cloud-rg
AZURE_LOCATION=eastus                    # Default: eastus
AZURE_TENANT_ID=...                      # Optional: Service principal
AZURE_CLIENT_ID=...                      # Optional: Service principal
AZURE_CLIENT_SECRET=...                  # Optional: Service principal

# Logging
LOG_LEVEL=info                           # Options: debug, info, success, warn, error

User Preferences

You can set default preferences:

import { getConfigManager } from './src/utils/config.js';

const config = getConfigManager();

// Set default cloud provider
config.setDefaultCloud('aws');

// Enable auto-approval (skip confirmation)
config.setAutoApprove(true);

// Set preferred regions
config.setPreferredRegion('aws', 'us-west-2');
config.setPreferredRegion('gcp', 'europe-west1');
config.setPreferredRegion('azure', 'westus2');

Troubleshooting

Common Issues

"Authentication Failed"

AWS:

# Check AWS credentials
aws sts get-caller-identity

# Reconfigure
aws configure

GCP:

# Check authentication status
gcloud auth list

# Reauthenticate
gcloud auth login

Azure:

# Check login status
az account show

# Relogin
az login

"AI API Key Not Found"

Make sure you've set either the OPENAI_API_KEY or GOOGLE_GENERATIVE_AI_API_KEY environment variable:

# Option 1: Add OpenAI key to .env file
echo "OPENAI_API_KEY=sk-your-key-here" >> .env

# Option 2: Add Gemini key to .env file
echo "GOOGLE_GENERATIVE_AI_API_KEY=your-key-here" >> .env

# Or export temporarily
export OPENAI_API_KEY=sk-your-key-here
# OR
export GOOGLE_GENERATIVE_AI_API_KEY=your-key-here

"Command Not Found: cloud-agent"

Ensure the package is linked globally:

cd /path/to/agent-cloud
pnpm link --global

Deployment Takes Too Long

This is normal! Cloud deployments can take 2-5 minutes depending on:

  • Cloud provider
  • Resource creation
  • Container builds
  • Network latency

Watch the logs for progress:

tail -f .agent-cloud/logs/deployment-*.log

Project Structure

agent-cloud/
├── bin/
│   └── cli.ts                    # CLI entry point
├── src/
│   ├── cli/
│   │   ├── index.ts              # CLI commands
│   │   └── workflow-commands.ts  # Workflow commands
│   ├── mastra/
│   │   ├── agents/
│   │   │   └── index.ts          # AI agents (Validator, Analyzer, Deployment)
│   │   ├── workflows/
│   │   │   └── deployment.ts     # Deployment workflow
│   │   └── index.ts              # Mastra instance
│   ├── providers/
│   │   ├── aws/index.ts          # AWS provider
│   │   ├── gcp/index.ts          # GCP provider
│   │   └── azure/index.ts        # Azure provider
│   └── utils/
│       ├── logger.ts             # Logging system
│       ├── error-handler.ts      # Error handling
│       └── config.ts             # Configuration management
├── .agent-cloud/
│   ├── logs/                     # Deployment logs
│   └── config.json               # Configuration & history
├── .env                          # Environment variables
├── package.json
└── README.md

Security Best Practices

  1. Never commit credentials - Use environment variables
  2. Use IAM roles - When deploying from CI/CD
  3. Rotate API keys - Regularly update OpenAI and cloud keys
  4. Review logs - Check .agent-cloud/logs/ for sensitive data
  5. Use service principals - For production Azure deployments
  6. Enable MFA - On all cloud accounts

Contributing

We welcome contributions! Here's how to get started:

# Fork the repository
# Clone your fork
git clone https://github.com/intojhanurag/agent-cloud.git

# Create a feature branch
git checkout -b feature/amazing-feature

# Make your changes and commit
git commit -m "Add amazing feature"

# Push to your fork
git push origin feature/amazing-feature

# Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

Built with:

Support

Roadmap

  • Support for more cloud providers (DigitalOcean, Cloudflare)
  • Rollback capabilities
  • Multi-region deployments
  • Database provisioning
  • CI/CD integration templates
  • Web UI dashboard
  • Terraform export
  • Cost optimization recommendations

Built with ❤️ by ojha_verse

Star us on GitHub if you find this useful!

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A intelligent CLI tool that analyzes your project and deploys it to AWS, GCP, or Azure with human-in-the-loop validation.

agent-cloud-vert.vercel.app/

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