{
  "mcpServers": {
    "kubeopt": {
      "command": "/path/to/kubeopt/.venv/bin/python3",
      "args": ["-m", "mcp_server.server"],
      "env": {
        "KUBEOPT_API_URL": "http://localhost:5001",
        "KUBEOPT_USERNAME": "kubeopt",
        "KUBEOPT_PASSWORD": "your-password"
      }
    }
  }
}

{
  "kubeopt": {
    "command": "/path/to/kubeopt/.venv/bin/python3",
    "args": ["-m", "mcp_server.server"],
    "env": {
      "KUBEOPT_API_URL": "http://localhost:5001",
      "KUBEOPT_USERNAME": "kubeopt",
      "KUBEOPT_PASSWORD": "your-password"
    }
  }
}

{
  "mcpServers": {
    "kubeopt": {
      "command": "/path/to/kubeopt/.venv/bin/python3",
      "args": ["-m", "mcp_server.server"],
      "env": {
        "KUBEOPT_API_URL": "http://localhost:5001",
        "KUBEOPT_USERNAME": "kubeopt",
        "KUBEOPT_PASSWORD": "your-password"
      }
    }
  }
}

What are my top 3 cost savings opportunities across all clusters?
Which pods are costing the most in the production namespace?
Give me a summary of total Kubernetes spend this month.
What's the optimization score for my staging cluster?
Trigger a fresh analysis on cluster prod-aks-eastus and report back.

## KubeOpt Cost Scan — 2026-04-27

| Cluster          | Provider | Monthly Spend | Savings Available |
|------------------|----------|---------------|-------------------|
| prod-eks-us-east | AWS      | $4,120        | $890/mo           |
| staging-aks-weu  | Azure    | $1,340        | $210/mo           |

**Total potential savings: $1,100/mo**

<details>
<summary>Top opportunities</summary>

1. $540/mo — prod-eks-us-east — Rightsize 6 over-provisioned node groups
2. $350/mo — prod-eks-us-east — Enable HPA on 4 deployments with static replicas
3. $210/mo — staging-aks-weu  — Remove 3 idle nodes outside business hours

</details>

name: K8s Cost Scan

on:
  pull_request:
    types: [opened, synchronize]
  schedule:
    - cron: '0 8 * * 1'   # Every Monday at 08:00 UTC
  workflow_dispatch:

permissions:
  contents: read
  pull-requests: write

jobs:
  cost-scan:
    name: KubeOpt Cost Scan
    runs-on: ubuntu-latest
    steps:
      - name: Run KubeOpt cost scan
        id: kubeopt
        uses: kubeopt/kubeopt@v1
        with:
          kubeopt-url:      ${{ secrets.KUBEOPT_URL }}
          kubeopt-username: ${{ secrets.KUBEOPT_USERNAME }}
          kubeopt-password: ${{ secrets.KUBEOPT_PASSWORD }}
          top:              5
          post-comment:     ${{ github.event_name == 'pull_request' && 'true' || 'false' }}

      - name: Print savings to log
        if: always()
        run: echo "Total savings available: ${{ steps.kubeopt.outputs.total-savings }}/mo"

- uses: kubeopt/kubeopt@v1
  with:
    kubeopt-url:      ${{ secrets.KUBEOPT_URL }}
    kubeopt-username: ${{ secrets.KUBEOPT_USERNAME }}
    kubeopt-password: ${{ secrets.KUBEOPT_PASSWORD }}
    cluster-id:       prod-eks-us-east-1
    top:              10

                         KubeOpt Platform
 +----------------------------------------------------------+
 |                                                          |
 |   React SPA (Recharts)     FastAPI REST API (v2)         |
 |   frontend/dist/           presentation/api/v2/          |
 |                                                          |
 +---------------------------+------------------------------+
                             |
          +------------------+------------------+
          |                  |                  |
  +-------v------+  +-------v------+  +--------v-------+
  |  Algorithms  |  |  Analytics   |  |  ML Models     |
  |  (16 modules)|  |  Collectors  |  |  Anomaly Det.  |
  |  rightsizing |  |  Processors  |  |  CPU Optimizer |
  |  HPA, storage|  |  Scorer      |  |  Workload Cls  |
  +--------------+  +--------------+  +----------------+
          |                  |                  |
  +-------v------------------v------------------v-------+
  |              Cloud Provider Abstraction              |
  |  6 interfaces: Auth, Executor, Metrics, Costs,      |
  |                Accounts, Inspector                   |
  +---+-----------------+-----------------+-------------+
      |                 |                 |
  +---v---+        +----v----+       +----v----+
  | Azure |        |   AWS   |       |   GCP   |
  | (AKS) |        |  (EKS)  |       |  (GKE)  |
  +-------+        +---------+       +---------+

# Clone and install
git clone https://github.com/kubeopt/kubeopt.git
cd kubeopt
pip install -r requirements.txt

# Set up credentials (copy and fill in your values)
cp .env.example .env

# Build frontend
cd frontend && npm install && npm run build && cd ..

# Run
python main.py
# Open http://localhost:5001

docker build -t kubeopt .
docker run -p 5001:5001 --env-file .env kubeopt

npx kubeopt clusters          # List clusters
npx kubeopt analyze <id>      # Run analysis
npx kubeopt report <id>       # View report

AZURE_SUBSCRIPTION_ID=your-subscription-id
AZURE_CLIENT_ID=your-client-id
AZURE_CLIENT_SECRET=your-client-secret
AZURE_TENANT_ID=your-tenant-id

AWS_ACCESS_KEY_ID=your-access-key
AWS_SECRET_ACCESS_KEY=your-secret-key
AWS_DEFAULT_REGION=us-east-1

GCP_SERVICE_ACCOUNT_KEY={"type":"service_account",...}
GCP_BILLING_DATASET=your_billing_dataset
GCP_BILLING_ACCOUNT_ID=your-billing-account-id

kubeopt/
  algorithms/          16 optimization algorithm modules
  analytics/           Cost collectors, processors, cluster scorer
  application/         Orchestrator, command generators
  infrastructure/
    cloud_providers/   Azure, AWS, GCP adapters (6 interfaces each)
    services/          Auth, caching, license validation, settings
    persistence/       Database, analysis engine
  machine_learning/    Anomaly detection, CPU optimizer, workload classifier
  presentation/
    api/v2/            FastAPI routers, schemas, dependencies
  frontend/            React SPA (TypeScript, Recharts, Tailwind)
  shared/
    standards/         16 YAML-based optimization standards
    config/            Application configuration
  mcp_server/          MCP server (6 tools, stdio transport)