# Usage Examples
Real-world examples of using the Azure Pricing MCP Server with AI assistants.
## Quick Start Guide
This guide demonstrates how to use natural language queries with the Azure Pricing MCP Server. Each example shows:
- The query you can ask
- Which tool is invoked
- Sample response format
Copy these queries directly or adapt them to your needs.
## Table of Contents
**Core Pricing**
- [Basic Price Queries](#basic-price-queries)
- [Cost Estimations](#cost-estimations)
- [Price Comparisons](#price-comparisons)
**Advanced Features**
- [Reserved Instance Pricing](#reserved-instance-pricing)
- [Region Recommendations](#region-recommendations)
- [Multi-Node & Cluster Pricing](#multi-node--cluster-pricing)
- [Spot VM Tools](#spot-vm-tools)
- [Orphaned Resource Detection](#orphaned-resource-detection)
- [PTU Sizing](#ptu-sizing)
**Discovery & Reference**
- [SKU Discovery](#sku-discovery)
- [Storage Pricing](#storage-pricing)
- [Retirement Warnings](#retirement-warnings)
- [Reference Tables](#reference-tables)
## Basic Price Queries
Query prices for Azure services using natural language. The `azure_price_search` tool handles all basic pricing queries.
### Virtual Machines
**Query:** "What's the price of a Standard_D4s_v3 VM in East US?"
**Response:**
```
Standard_D4s_v3 in East US:
- Linux: $0.192/hour ($140.16/month)
- Windows: $0.384/hour ($280.32/month)
- 1-Year Savings Plan: $0.134/hour (30% savings)
- 3-Year Savings Plan: $0.106/hour (45% savings)
```
### Databases
**Query:** "What are the prices for Azure SQL Database in West Europe?"
The tool filters by `service_name=Azure SQL Database` and `region=westeurope`.
### GPU VMs
**Query:** "Show me NVIDIA GPU VM pricing in East US 2"
Searches for VM SKUs with `NC` series (NVIDIA GPUs) in the specified region.
---
## Cost Estimations
Estimate monthly and yearly costs based on usage patterns. Use the `azure_cost_estimate` tool.
### Development Environment (Part-Time Usage)
**Query:** "Estimate monthly cost for D4s_v5 running 10 hours per day, 22 days per month"
**Response:**
```
D4s_v5 Cost Estimate (East US)
Usage: 220 hours/month
On-Demand: $42.24/month ($506.88/year)
1-Year Plan: $29.48/month ($353.76/year) - Save 30%
3-Year Plan: $23.32/month ($279.84/year) - Save 45%
```
### Production 24/7 Workload
**Query:** "Estimate yearly cost for E8s_v5 running 24/7 in West US 2"
Calculates for 730 hours/month (24/7 operation).
---
## Price Comparisons
Compare costs across regions or between SKUs using `azure_price_compare`.
### Compare Across Regions
**Query:** "Compare D4s_v5 VM prices between eastus, westeurope, and southeastasia"
**Response:**
```
D4s_v5 Price Comparison:
| Region | Hourly | Monthly (730h) | vs Cheapest |
|---------------|----------|----------------|-------------|
| eastus | $0.192 | $140.16 | Cheapest |
| westeurope | $0.211 | $154.03 | +10% |
| southeastasia | $0.221 | $161.33 | +15% |
```
### Compare Storage Tiers
**Query:** "Compare storage options: Premium SSD vs Standard SSD vs Standard HDD"
Compares pricing and performance characteristics of different storage types.
---
## Reserved Instance Pricing
Compare Reserved Instance (RI) pricing with on-demand rates. Use the `azure_ri_pricing` tool for break-even analysis.
**Query:** "Show me Reserved Instance pricing for D4s v3 in East US"
**Response:**
```
D4s v3 (East US) - Reserved Instance Analysis
1-Year RI:
Rate: $0.112/hr (vs $0.192/hr on-demand)
Savings: 41.5%
Break-even: 7.0 months
Annual savings: $700.80
3-Year RI:
Rate: $0.073/hr (vs $0.192/hr on-demand)
Savings: 62.0%
Break-even: 13.7 months
Annual savings: $1,042.44
```
---
## Multi-Node & Cluster Pricing
Calculate costs for node pools and entire Kubernetes clusters.
### AKS Node Pool
**Query:** "Price for 20 Standard_D32s_v6 nodes in East US 2 for AKS"
**Response:**
```
Standard_D32s_v6 in East US 2 (20 nodes):
| Option | Per Node/Month | 20 Nodes/Month | Savings |
|-----------------|----------------|----------------|---------|
| Linux On-Demand | $1,177 | $23,550 | - |
| 1-Year Plan | $812 | $16,250 | 31% |
| 3-Year Plan | $542 | $10,833 | 54% |
| Linux Spot | $228 | $4,569 | 81% |
```
### Kubernetes Cluster
**Query:** "Estimate monthly cost for a Kubernetes cluster with 5 D8s_v5 nodes for system and 20 D16s_v5 nodes for workloads in East US"
Combines pricing for multiple node pools.
---
## Region Recommendations
Find the most cost-effective Azure regions using `azure_region_recommend`.
**Flexible Format:** Accepts SKU names in multiple formats:
- Display: `D4s v5`, `E4as v5`
- ARM: `Standard_D4s_v5`, `Standard_E4as_v5`
- Underscore: `D4s_v5`, `E4as_v5`
### Find Cheapest Regions
**Query:** "What are the cheapest regions for D4s v5 VMs?"
**Response:**
```
Region Recommendations for D4s v5 (USD)
Cheapest: IN Central (centralindia) - $0.0234/hr
Most Expensive: BR South (brazilsouth) - $0.1170/hr
Max Savings: 80.0%
Top 5 Regions:
| Rank | Region | Location | Price/hr | Savings |
|------|----------------|---------------|----------|---------|
| 1 | centralindia | IN Central | $0.0234 | 80.0% |
| 2 | eastus2 | US East 2 | $0.0336 | 71.2% |
| 3 | eastus | US East | $0.0336 | 71.2% |
| 4 | westus3 | US West 3 | $0.0336 | 71.2% |
| 5 | northcentralus | US North Cen | $0.0364 | 68.9% |
```
### With Discount
**Query:** "Show cheapest regions for E4s v5 VMs with my 15% enterprise discount"
Applies your discount percentage to all prices shown.
---
## SKU Discovery
Discover available Azure services and SKUs using fuzzy matching with `azure_sku_discovery`.
### Find VM Sizes
**Query:** "What VM sizes are available for compute-intensive workloads?"
Searches for compute-optimized VM series.
### App Service Plans
**Query:** "What App Service plans are available?"
**Response:**
```
Azure App Service Plans:
Basic:
• B1: $0.018/hour
• B2: $0.036/hour
• B3: $0.072/hour
Standard:
• S1: $0.10/hour
• S2: $0.20/hour
• S3: $0.40/hour
Premium v3:
• P1v3: $0.125/hour
• P2v3: $0.25/hour
• P3v3: $0.50/hour
```
### Common Service Aliases
The tool recognizes common aliases:
| You Say | Finds |
|---------|-------|
| "vm", "virtual machine" | Virtual Machines |
| "app service", "web app" | Azure App Service |
| "sql", "database" | Azure SQL Database |
| "kubernetes", "aks", "k8s" | Azure Kubernetes Service |
| "storage", "blob" | Storage |
| "functions", "serverless" | Azure Functions |
---
## Storage Pricing
Query storage costs for various Azure storage services.
### Block Blob Operations
**Query:** "How much does 100,000 write operations on Block Blob LRS GPv1 in East US cost?"
**Response:**
```
Block Blob LRS (GPv1) - East US:
Write Operations: $0.00036 per 10K
100,000 operations = 10 × 10K = $0.0036
With 10% discount: $0.00324
```
### Storage Tiers
**Query:** "Compare Hot, Cool, and Archive storage pricing in East US"
Compares data storage and access costs across tiers.
---
## Spot VM Tools
**Note:** Requires Azure authentication (`az login`, service principal, or managed identity).
### Check Eviction Rates
**Query:** "What are the Spot eviction rates for D4s_v3 in East US?"
Uses `spot_eviction_rates` to query Azure Resource Graph for real-time eviction data.
**Response:**
```
Spot VM Eviction Rates (East US):
| SKU | Eviction Rate | Risk Level |
|--------|---------------|------------|
| D4s_v3 | 0-5% | Low |
| D8s_v3 | 5-10% | Moderate |
```
### Price History
**Query:** "Show me the Spot price history for D4s_v3 in East US over the last 30 days"
Uses `spot_price_history` for up to 90 days of historical pricing.
**Response:**
```
Spot Price History - D4s_v3 (East US):
Current: $0.0384/hr
7-day avg: $0.0391/hr
30-day avg: $0.0402/hr
Range: $0.0362 - $0.0458
Trend: Stable (±5%)
```
### Simulate Eviction
**Query:** "Simulate eviction for my Spot VM my-spot-vm in my-rg"
Uses `simulate_eviction` to trigger a test eviction signal (requires VM Contributor role).
### Decision Analysis
**Query:** "Should I use Spot VMs for D16s_v3 in East US for batch processing?"
Combines eviction rates and pricing to provide recommendations:
```
D16s_v3 (East US) Analysis:
Eviction Risk: 0-5% (Low)
Best for: Batch processing, CI/CD, dev/test
Cost Comparison:
| Type | Monthly (730h) | Savings |
|-----------|----------------|---------|
| On-Demand | $560.64 | - |
| Spot | $112.42 | 80% |
| 1-Year RI | $354.78 | 37% |
Recommendation: Spot VMs recommended for batch processing
```
---
## Orphaned Resource Detection
**Note:** Requires Azure authentication (`az login`, service principal, or managed identity).
Detect orphaned Azure resources that are incurring costs without providing value. Uses `find_orphaned_resources` tool.
### Scan All Subscriptions
**Query:** "Find all orphaned resources across my Azure subscriptions"
**Response:**
```
### Orphaned Resource Report
Total orphaned resources: 5
Estimated wasted cost (60 days): $127.50 USD
Subscriptions scanned: 3
#### Summary by Type
| Resource Type | Count | Est. Cost |
|---------------|-------|-----------|
| Unattached Disk | 2 | $85.00 |
| Orphaned Public IP | 2 | $42.50 |
| Orphaned NSG | 1 | $0.00 |
```
### Custom Lookback Period
**Query:** "Show me orphaned resources with costs from the last 30 days"
Uses `days=30` parameter to adjust the cost calculation window.
### Single Subscription Scan
**Query:** "Scan for orphaned resources in my primary subscription only"
Uses `all_subscriptions=false` to limit the scan scope.
### Detected Resource Types
The tool detects these orphaned resource types:
| Resource Type | Detection Criteria |
|---------------|--------------------|
| **Unattached Disk** | Managed disks with no `managedBy` reference |
| **Orphaned NIC** | Network interfaces not attached to a VM or private endpoint |
| **Orphaned Public IP** | Public IPs not associated with any resource |
| **Orphaned NSG** | Network security groups not attached to any NIC or subnet |
| **Empty App Service Plan** | App Service Plans with zero hosted apps |
### Cost Analysis
**Query:** "How much am I wasting on orphaned resources?"
**Response:**
```
### Orphaned Resource Report
Total orphaned resources: 3
Estimated wasted cost (60 days): $89.25 USD
#### Unattached Disk (2)
| Name | Resource Group | Location | Cost |
|------|----------------|----------|------|
| old-data-disk | prod-rg | eastus | $52.00 |
| temp-backup | dev-rg | westus2 | $30.00 |
#### Orphaned Public IP (1)
| Name | Resource Group | Location | Cost |
|------|----------------|----------|------|
| unused-pip | test-rg | eastus | $7.25 |
```
---
## PTU Sizing
Estimate Provisioned Throughput Units (PTUs) for Azure OpenAI / AI Foundry model deployments. Uses `azure_ptu_sizing` tool.
**No authentication required** - PTU calculations are purely offline using official Microsoft data.
The tool needs three required inputs: **RPM** (requests per minute), **avg input tokens**, and **avg output tokens** per request. Here's how to get them.
### Getting Your Input Data
#### Option A — Azure CLI (no Log Analytics)
Copy-paste this script — it queries the last 30 days and prints your three inputs:
```bash
# Replace {sub}, {rg}, {name} with your values
RES="/subscriptions/{sub}/resourceGroups/{rg}/providers/Microsoft.CognitiveServices/accounts/{name}"
START=$(date -u -d "30 days ago" +%Y-%m-%dT%H:%M:%SZ)
END=$(date -u +%Y-%m-%dT%H:%M:%SZ)
REQS=$(az monitor metrics list --resource "$RES" --metric AzureOpenAIRequests \
--aggregation Total --interval P30D --start-time "$START" --end-time "$END" \
--query "value[0].timeseries[0].data[0].total" -o tsv)
INPUT=$(az monitor metrics list --resource "$RES" --metric ProcessedPromptTokens \
--aggregation Total --interval P30D --start-time "$START" --end-time "$END" \
--query "value[0].timeseries[0].data[0].total" -o tsv)
OUTPUT=$(az monitor metrics list --resource "$RES" --metric GeneratedTokens \
--aggregation Total --interval P30D --start-time "$START" --end-time "$END" \
--query "value[0].timeseries[0].data[0].total" -o tsv)
PEAK=$(az monitor metrics list --resource "$RES" --metric AzureOpenAIRequests \
--aggregation Total --interval PT1H --start-time "$START" --end-time "$END" \
--query "max(value[0].timeseries[0].data[].total)" -o tsv)
echo "=== Your PTU Sizing Inputs ==="
echo "rpm: $(echo "$PEAK / 60" | bc)"
echo "avg_input_tokens: $(echo "$INPUT / $REQS" | bc)"
echo "avg_output_tokens: $(echo "$OUTPUT / $REQS" | bc)"
```
#### Option B — KQL (requires Log Analytics)
Enable diagnostic settings on your OpenAI resource → send to Log Analytics, then run:
```kql
AzureMetrics
| where ResourceProvider == "MICROSOFT.COGNITIVESERVICES"
| where TimeGenerated >= ago(30d)
| summarize
TotalRequests = sumif(Total, MetricName == "AzureOpenAIRequests"),
TotalInputTok = sumif(Total, MetricName == "ProcessedPromptTokens"),
TotalOutputTok = sumif(Total, MetricName == "GeneratedTokens")
by bin(TimeGenerated, 1h)
| summarize
AvgRPM = avg(TotalRequests) / 60,
PeakRPM = max(TotalRequests) / 60,
AvgInputTokens = avg(TotalInputTok / TotalRequests),
AvgOutputTokens= avg(TotalOutputTok / TotalRequests)
```
Use `PeakRPM` to size for burst traffic.
#### No Azure Data Yet?
| Use Case | Typical RPM | Avg Input Tokens | Avg Output Tokens |
|----------|:-----------:|:----------------:|:-----------------:|
| Chatbot / Q&A | 30–100 | 200–500 | 100–300 |
| RAG (retrieval-augmented) | 20–80 | 1,500–3,000 | 300–600 |
| Document summarization | 10–30 | 3,000–6,000 | 500–1,000 |
| Code generation | 20–60 | 1,000–2,000 | 500–1,500 |
| Batch processing | 50–200 | 500–1,500 | 200–500 |
> Start conservative — you can always scale PTUs up later.
### Basic PTU Estimation
**Query:** "How many PTUs do I need for gpt-4.1 at 100 RPM with 500 input and 200 output tokens?"
**Response:**
```
⚡ PTU Sizing Estimate
Model: gpt-4.1
Deployment: Global Provisioned
Workload Shape:
- Requests/min: 100
- Input tokens/request: 500
- Output tokens/request: 200
Calculation:
- Output multiplier: 1 output = 4 input tokens
- Equivalent TPM: 130,000
- Input TPM per PTU: 3,000
- Raw PTU estimate: 43.33
✅ Recommended PTUs: 45
(Minimum: 15, Scale increment: 5)
```
### With Caching
**Query:** "Estimate PTUs for gpt-5 with 50 RPM, 1000 input tokens, 500 output tokens, and 300 cached tokens using DataZoneProvisioned"
**Response:**
```
⚡ PTU Sizing Estimate
Model: gpt-5
Deployment: Data Zone Provisioned
Workload Shape:
- Requests/min: 50
- Input tokens/request: 1,000
- Output tokens/request: 500
- Cached tokens/request: 300
Calculation:
- Output multiplier: 1 output = 8 input tokens (gpt-5 specific)
- Effective input (after cache): 700
- Equivalent TPM: 235,000
✅ Recommended PTUs: 50
```
### Regional Deployment
**Query:** "Calculate PTUs for o4-mini Regional deployment at 200 RPM with 300 input and 150 output tokens"
Uses different minimum PTUs and scale increments for Regional deployments.
### With Cost Estimation
**Query:** "Estimate PTU cost for gpt-4o in eastus with 400 RPM, 300 input tokens, 400 output tokens"
Uses `include_cost=true` to fetch live $/PTU/hr pricing.
### Supported Models
| Model Family | Models |
|-------------|--------|
| **GPT-5.x** | gpt-5.2, gpt-5.1, gpt-5, gpt-5-mini, codex variants |
| **GPT-4.1** | gpt-4.1, gpt-4.1-mini, gpt-4.1-nano |
| **GPT-4o** | gpt-4o, gpt-4o-mini |
| **O-series** | o3, o4-mini, o3-mini, o1 |
| **Direct Azure** | Llama-3.3-70B-Instruct, DeepSeek-R1, DeepSeek-R1-0528, DeepSeek-V3-0324 |
### Deployment Types
| Type | Processing | Min/Increment |
|------|------------|---------------|
| **GlobalProvisioned** | Any Azure geography | Lowest minimums |
| **DataZoneProvisioned** | Within data zone (EU, US) | Same as Global |
| **RegionalProvisioned** | Single region | Higher minimums |
---
## Retirement Warnings
The server automatically warns when querying retired or retiring VM SKUs.
### Retiring SKU Example
**Query:** "What's the price of L32s v2 in East US?"
**Response:**
```
⚠️ RETIREMENT WARNING: Lsv2-series
Status: Retirement Announced
Retirement Date: 11/15/28
Recommendation: Migrate to Lsv3, Lasv3, Lsv4, or Lasv4 series
L32s v2 in East US:
- Spot: $0.313/hour
- On-Demand: $2.480/hour
```
### Previous Generation Example
**Query:** "What's the price of E32 v3 in East US?"
**Response:**
```
ℹ️ PREVIOUS GENERATION: Ev3-series
Recommendation: Consider upgrading to Ev5 or Ev6 series
E32 v3 in East US: $2.016/hour
```
### Warning Types
| Status | Meaning |
|--------|---------|
| ⚠️ Retirement Announced | SKU will be retired - plan migration |
| 🚫 Retired | No longer available for new deployments |
| ℹ️ Previous Generation | Newer versions available |
---
## Reference Tables
Quick reference for service names, regions, and best practices.
### Common Azure Service Names
Service names are case-sensitive. Use exact names for best results.
| Service | API Name |
|---------|----------|
| Virtual Machines | `Virtual Machines` |
| Storage | `Storage` |
| SQL Database | `Azure SQL Database` |
| Cosmos DB | `Azure Cosmos DB` |
| Kubernetes | `Azure Kubernetes Service` |
| App Service | `Azure App Service` |
| Functions | `Azure Functions` |
| OpenAI | `Azure OpenAI` |
### Common Azure Regions
| Region Code | Location |
|-------------|----------|
| `eastus` | US East |
| `eastus2` | US East 2 |
| `westus2` | US West 2 |
| `centralus` | US Central |
| `westeurope` | West Europe |
| `northeurope` | North Europe |
| `uksouth` | UK South |
| `eastasia` | East Asia |
| `southeastasia` | Southeast Asia |
| `japaneast` | Japan East |
### Best Practices
| Practice | Why |
|----------|-----|
| Use specific SKU names | `D4s_v5` not `D4` - avoids ambiguity |
| Use lowercase region codes | API requires `eastus` not `East US` |
| Compare savings plans | 1yr and 3yr options can save 30-60% |
| Try fuzzy discovery | `azure_sku_discovery` finds services with approximate names |
| Specify currency | Add `currency_code=EUR` for non-USD pricing |
---
## Troubleshooting
### No Results
- Service name misspelled or wrong case
- SKU doesn't exist in that region
- Region code incorrect (use lowercase)
**Solution:** Start with broader search, then add filters.
### Unexpected Prices
- Check Spot vs On-Demand pricing
- Windows pricing is ~2x Linux
- Verify unit (per-hour vs per-month)
### Too Many Results
- Add region or SKU name filters
- Use `limit` parameter
---
**Questions?** Check the [README](../README.md) or open an [issue](https://github.com/msftnadavbh/AzurePricingMCP/issues).
