GCP成本估算服务

graph TB
    guide["get_estimation_guide<br/>─────────────────<br/>IN: service_name<br/>OUT: required params, pricing<br/>factors, free tier info, tips<br/>─────────────────<br/>Internally resolves<br/>service &amp; SKU lookup"]

    classify["classify_resource_cost<br/>─────────────────<br/>IN: Terraform resource type,<br/>resource attributes<br/>OUT: billing trigger, SKU,<br/>warnings, monthly estimate"]

    services["list_services<br/>─────────────────<br/>IN: name filter (opt)<br/>OUT: service_id, display_name"]

    skus["list_skus<br/>─────────────────<br/>IN: service_id, region, keyword<br/>OUT: sku_id, display_name,<br/>categories, regions"]

    price["get_sku_price<br/>─────────────────<br/>IN: sku_id, currency<br/>OUT: price/unit, pricing tiers"]

    cost["estimate_cost<br/>─────────────────<br/>IN: sku_id, usage_amount<br/>OUT: estimated cost with<br/>automatic free tier deduction<br/>─────────────────<br/>Internally resolves pricing"]

    services -- "service_id" --> skus
    skus -- "sku_id" --> price
    skus -- "sku_id" --> cost

{
  "resource_type": "google_license_manager_configuration.office",
  "product": "Office2021ProfessionalPlus",
  "license_count": 10
}

gcloud auth application-default login

brew tap nozomi-koborinai/tap
brew install gcp-cost-mcp-server

# Update tap to fetch the latest Formula
brew update

# Check the available version
brew info gcp-cost-mcp-server

# Upgrade to the latest version
brew upgrade gcp-cost-mcp-server

git clone https://github.com/nozomi-koborinai/gcp-cost-mcp-server.git
cd gcp-cost-mcp-server
go build -o gcp-cost-mcp-server .

# If installed via Homebrew
which gcp-cost-mcp-server
# Output: /opt/homebrew/bin/gcp-cost-mcp-server (Apple Silicon)
#         /usr/local/bin/gcp-cost-mcp-server (Intel/Linux)

{
  "mcpServers": {
    "gcp-cost": {
      "command": "/opt/homebrew/bin/gcp-cost-mcp-server"
    }
  }
}

{
  "mcpServers": {
    "gcp-cost": {
      "command": "/opt/homebrew/bin/gcp-cost-mcp-server"
    }
  }
}

{
  "mcpServers": {
    "gcp-cost": {
      "command": "/opt/homebrew/bin/gcp-cost-mcp-server"
    }
  }
}

You: "How much would Cloud Run cost for 2 instances?"

AI: "To estimate Cloud Run costs accurately, I need a few more details:
    - Region: Where will this be deployed? (e.g., asia-northeast1, us-central1)
    - vCPU: How many vCPUs per instance? (e.g., 1, 2, 4)
    - Memory: How much memory per instance? (e.g., 1 GiB, 2 GiB)
    - Billing type: Instance-based or request-based?
    - Monthly usage: Will it run 24/7 (730 hours) or less?"

You: "Tokyo region, 1 vCPU, 2GB memory, instance-based, 24/7"

AI: "Based on your requirements for 2 Cloud Run instances in Tokyo (asia-northeast1):

    📊 Cost Breakdown:
    - vCPU: 2 vCPU × 2,628,000 sec = 5,256,000 vCPU-seconds
      Free tier applied: -180,000 vCPU-seconds
      Billable: 5,076,000 vCPU-seconds × $0.000024 = $121.82/month
    
    - Memory: 4 GiB × 2,628,000 sec = 10,512,000 GiB-seconds
      Free tier applied: -360,000 GiB-seconds
      Billable: 10,152,000 GiB-seconds × $0.0000025 = $25.38/month
    
    💰 Total estimated: ~$147.20/month (free tier already applied)
    
    💡 Tip: Cloud Run's free tier (180,000 vCPU-sec + 360,000 GiB-sec/month) 
       has been automatically deducted from your estimate."

You: "What's the service ID for Compute Engine?"
You: "List the available SKUs for Compute Engine in Tokyo region"
You: "How much would an n2-standard-4 instance cost for 730 hours?"

You: "How much would Vertex AI cost for my ML training?"

AI: "I'll generate an estimation guide for Vertex AI by analyzing available SKUs...
    
    Based on my analysis, to estimate Vertex AI costs, I need:
    1. Region: Where will training run?
    2. Machine type: What accelerator type? (e.g., NVIDIA T4, A100)
    3. Training hours: How long will training take?
    4. Storage: How much training data?
    
    Free tier note: Vertex AI offers $300 in free credits for new users.
    
    Would you like me to list the specific SKUs available for Vertex AI?"

You: [Upload architecture diagram image]
     "Please estimate the monthly cost for this architecture"

AI: "I've analyzed your architecture diagram. Here are the GCP services identified:
     - Cloud Run (Application layer)
     - Cloud SQL (Database)
     - Cloud Storage (Static files)
     - Cloud Load Balancing (Traffic distribution)
     
     To provide an accurate estimate, I need some details:
     
     🌏 Common Settings:
     - Region: Is asia-northeast1 (Tokyo) okay?
     
     📦 Cloud Run:
     - vCPUs: 1? 2? 4?
     - Memory: 1GB? 2GB? 4GB?
     - Instance count: How many instances?
     - Uptime: 24/7 or specific hours only?
     
     🗄️ Cloud SQL:
     - Database type: MySQL? PostgreSQL?
     - Machine type: Dev (db-f1-micro)? Production (db-custom-2-4096)?
     - Storage: How many GB needed?
     - High Availability (HA): Required?"

You: "Tokyo region, Cloud Run with 1vCPU/2GB × 2 instances running 24/7,
      Cloud SQL PostgreSQL db-custom-2-4096, 100GB SSD with HA,
      Cloud Storage 50GB Standard"

AI: "Thank you! Here's your estimate (free tiers automatically applied):

     | Service            | Configuration                  | Monthly Cost |
     |--------------------|--------------------------------|--------------|
     | Cloud Run          | 2 × 1vCPU × 2GB (24/7)         | $147.20 ✨   |
     | Cloud SQL          | PostgreSQL, 2vCPU/4GB, 100GB HA| $178.50      |
     | Cloud Storage      | 50GB Standard                  | $0.00 ✨     |
     | Cloud Load Balancing| Base + traffic                | $18.00       |
     | **Total**          |                                | **$343.70**  |
     
     ✨ = Free tier applied
     
     💡 Cost Optimization Tips:
     - Cloud Run: Set min instances to 0 to reduce idle costs
     - Cloud SQL: Disable HA for ~50% savings (dev environments)
     - Consider 1yr/3yr Committed Use Discounts (CUDs) for up to 57% off"

gcloud auth application-default login

{
  "mcpServers": {
    "gcp-cost": {
      "command": "/path/to/gcp-cost-mcp-server",
      "env": {
        "GOOGLE_APPLICATION_CREDENTIALS": "/path/to/service-account.json"
      }
    }
  }
}

gcp-cost-mcp-server/
├── main.go                      # Entry point, tool registration
├── internal/
│   ├── freetier/                # Free tier information retrieval
│   │   ├── service.go           # FreeTierService with 24h cache
│   │   ├── search.go            # DuckDuckGo search client
│   │   ├── scraper.go           # GCP documentation scraper
│   │   └── patterns.go          # Regex patterns for extraction
│   ├── pricing/
│   │   ├── client.go            # Cloud Billing Catalog API client
│   │   └── supplemental/        # Curated Catalog-absent pricing (License Manager / Office SPLA)
│   └── tools/
│       ├── deps.go                  # Consumer-side interfaces (PricingClient, FreeTierProvider)
│       ├── supplemental_client.go   # Merges supplemental catalog into PricingClient
│       ├── classify_resource_cost.go # Terraform resource cost classification
│       ├── get_estimation_guide.go  # Dynamic guide generator
│       ├── guide_builder.go         # SKU analysis for guide generation
│       ├── service_lookup.go        # Service name → service ID resolution
│       ├── estimate_cost.go         # Cost calc + free tier
│       ├── list_services.go
│       ├── list_skus.go
│       └── get_sku_price.go

flowchart TB
    subgraph MCP["MCP Server Tools"]
        direction TB

        Guide["get_estimation_guide<br/>─────────────────<br/>• Dynamic SKU analysis<br/>• Free tier info included<br/>• Self-contained"]
        Classify["classify_resource_cost<br/>─────────────────<br/>• Terraform resource rules<br/>• Existence-billing warnings<br/>• Monthly estimate when possible"]

        Services["list_services<br/>─────────────────<br/>Returns: service IDs"]
        SKUs["list_skus<br/>─────────────────<br/>Returns: SKU IDs, regions"]
        Price["get_sku_price<br/>─────────────────<br/>Returns: price/unit, tiers"]
        Cost["estimate_cost<br/>─────────────────<br/>• Auto free tier deduction<br/>• Tiered pricing support<br/>• Self-contained"]

        Services --> SKUs
        SKUs --> Price
        SKUs --> Cost
    end

    subgraph External["External Services"]
        Billing["Google Cloud Billing API v2beta<br/>cloudbilling.googleapis.com"]
        Docs["GCP Documentation<br/>(for free tier info)"]
        DDG["DuckDuckGo Search<br/>(fallback for doc discovery)"]
    end

    MCP --> Billing
    Guide -.-> Docs
    Guide -.-> DDG
    Cost -.-> Docs
    Cost -.-> DDG

sequenceDiagram
    participant User
    participant AI as AI Assistant
    participant MCP as MCP Server
    participant API as Cloud Billing API
    participant Docs as GCP Docs
    
    User->>AI: "How much would Cloud Run cost?"
    AI->>MCP: get_estimation_guide("Cloud Run")
    MCP->>API: ListSKUs(Cloud Run)
    API-->>MCP: SKU list
    MCP->>Docs: Fetch free tier info
    Docs-->>MCP: Free tier data
    MCP-->>AI: Dynamic guide + free tier
    AI->>User: "I need: region, vCPU, memory..."
    
    User->>AI: "Tokyo, 1vCPU, 2GB, 24/7"
    AI->>MCP: list_services()
    MCP->>API: ListServices
    API-->>MCP: Service IDs
    AI->>MCP: list_skus(service_id)
    MCP->>API: ListSKUs
    API-->>MCP: SKU details
    AI->>MCP: estimate_cost(sku_id, usage)
    MCP->>MCP: Apply free tier deduction
    MCP-->>AI: Cost with free tier applied
    AI->>User: "Estimated: $147.20/month (free tier applied)"

go build -o gcp-cost-mcp-server .

# Run all tests
go test -v ./...

# With coverage
go test -cover ./...

npx @modelcontextprotocol/inspector ./gcp-cost-mcp-server

# macOS (Apple Silicon)
GOOS=darwin GOARCH=arm64 go build -o dist/gcp-cost-mcp-server-darwin-arm64 .

# macOS (Intel)
GOOS=darwin GOARCH=amd64 go build -o dist/gcp-cost-mcp-server-darwin-amd64 .

# Linux (x86_64)
GOOS=linux GOARCH=amd64 go build -o dist/gcp-cost-mcp-server-linux-amd64 .

# Windows (x86_64)
GOOS=windows GOARCH=amd64 go build -o dist/gcp-cost-mcp-server-windows-amd64.exe .

# 1. Create and push a tag
git tag v0.6.0
git push origin v0.6.0

# Build
go build -o gcp-cost-mcp-server .

# Run locally
./gcp-cost-mcp-server

# Test GoReleaser config (dry run)
goreleaser release --snapshot --clean

// Genkit: Type-safe with auto-generated schema
genkit.DefineTool(g, "list_skus", "Lists SKUs for a service",
    func(ctx *ai.ToolContext, input struct {
        ServiceID string `json:"service_id" jsonschema_description:"The service ID"`
        PageSize  int    `json:"page_size,omitempty"`
    }) (*Output, error) {
        // Implementation
    })