Azure Pricing MCP Server 💰

A Model Context Protocol (MCP) server that provides AI assistants with real-time access to Azure retail pricing information. Query VM prices, compare costs across regions, estimate monthly bills, and discover available SKUs—all through natural language.

🚀 Quick Start

# Clone and setup
git clone https://github.com/msftnadavbh/AzurePricingMCP.git
cd AzurePricingMCP
python -m venv .venv
source .venv/bin/activate  # Windows: .venv\Scripts\activate
pip install -r requirements.txt

# Test the server
python -m azure_pricing_mcp

Then configure your AI assistant. See Integrations.

✨ Features

• Price Search - Query Azure prices with flexible filters

• Price Comparison - Compare costs across regions or SKUs

• Cost Estimation - Calculate monthly/yearly costs

• Reserved Instances - Compare RI pricing with break-even analysis

• Region Recommendations - Find the cheapest regions for any SKU

• SKU Discovery - Fuzzy matching for service names

• Retirement Warnings - Alerts for retiring VM SKUs

• Spot VM Intelligence - Eviction rates and price history (requires Azure auth)

• Orphaned Resources - Detect unused resources with real cost calculation (requires Azure auth)

• PTU Sizing - Estimate Provisioned Throughput Units for Azure OpenAI deployments

• Databricks DBU Pricing - Search DBU rates, estimate costs, compare workloads

• GitHub Pricing - Full GitHub pricing catalog + cost estimation (Plans, Copilot, Actions, Security)

📖 Full feature details →

🛠️ Tools

18 tools available for AI assistants:

• azure_price_search - Search retail prices

• azure_price_compare - Compare across regions/SKUs

• azure_ri_pricing - Reserved Instance pricing

• azure_cost_estimate - Usage-based cost estimation

• azure_region_recommend - Find cheapest regions

• azure_discover_skus / azure_sku_discovery - SKU lookup

• get_customer_discount - Customer discount information

• spot_eviction_rates / spot_price_history / simulate_eviction - Spot VM tools

• find_orphaned_resources - Detect orphaned resources with cost analysis

• azure_ptu_sizing - Estimate PTUs for Azure OpenAI deployments

• databricks_dbu_pricing / databricks_cost_estimate / databricks_compare_workloads - Databricks DBU pricing

• github_pricing / github_cost_estimate - GitHub pricing catalog and cost estimation

📖 Tool documentation →

📋 Installation

Docker (Easiest):

docker build -t azure-pricing-mcp .
docker run -i azure-pricing-mcp

Python:

pip install -r requirements.txt

📖 Full installation guide →

🔌 Integrations

Works with any MCP-compatible AI assistant:

• VS Code with GitHub Copilot

• Claude Desktop

📖 Integration setup →

📁 Project Structure

AzurePricingMCP/
├── src/azure_pricing_mcp/    # Main package
│   ├── server.py             # MCP server
│   ├── handlers.py           # Tool handlers
│   ├── client.py             # Azure API client
│   ├── config.py             # Pricing data & constants
│   ├── tools.py              # Core tool definitions
│   ├── formatters.py         # Response formatters
│   ├── models.py             # Data models
│   ├── services/             # Business logic
│   ├── databricks/           # Databricks DBU tools
│   └── github_pricing/       # GitHub pricing tools
├── tests/                    # Test suite (9 files, 236+ tests)
├── docs/                     # Documentation
└── scripts/                  # Setup & debug scripts

📖 Detailed structure →

🔌 API Reference

This server uses the Azure Retail Prices API:

https://prices.azure.com/api/retail/prices

No authentication required - The Azure Retail Prices API is publicly accessible.

🤝 Contributing

We welcome contributions! See CONTRIBUTING.md for setup instructions, code style, and PR process.

📚 Documentation

📄 License

MIT License - see LICENSE for details.

🙏 Acknowledgments

• Original Author: @charris-msft

• Current Maintainer: @msftnadavbh

• Contributors: @notoriousmic, @iditbnaya, @roy2392

• Model Context Protocol

• Azure Retail Prices API

📬 Support

• Issues: GitHub Issues

• Discussions: GitHub Discussions