Introducing Cost Management and Pricing Toolsets in Azure Resource Manager MCP Server

The Azure Resource Manager MCP server was recently launched to give AI agents first-class access to Azure infrastructure operations through the Azure control plane. Today, Microsoft Cost Management is releasing the Cost Management and Pricing toolsets within Azure Resource Manager MCP, bringing cost awareness directly into the workflows where cloud decisions are made.

Cloud operations and cloud economics are deeply connected, but the data required to make those decisions is often fragmented across different tools and experiences. By extending ARM MCP with cost management and pricing capabilities, AI agents can combine Azure resource information with cost, pricing, budget, and optimization insights, enabling more seamless and cost-aware cloud workflows.

What You Can Do Today

Plan Before You Deploy

Every cloud project starts with a series of tradeoffs. Before resources are deployed, teams need to understand how architectural decisions, resource choices, and regions will impact cost.

An AI agent can estimate costs, compare deployment options, and factor in negotiated rates where available so you can evaluate cost alongside technical requirements before deployment. 

Examples

• “How would my estimated monthly cost change if I updated the VM in this ARM template <path to template> from Standard_D8s_v5 to Standard_D2s_v5?"
• "Estimate the monthly cost of a three-node AKS cluster with my negotiated pricing.”

 

Understand Costs

Once workloads are running, cost visibility becomes the priority.  An AI agent can query your cost data to explain cost trends, changes in spend, and surface cost drivers.

Examples

• "What were my top cost drivers this month?"
•  "Which resource had the biggest cost increase this month vs. last?"

 

Manage Cloud Spend

With visibility in place, budget and alerts help teams avoid surprises. An AI agent can create and review budgets and check alerts so you can see where spend is tracking against your plans.

Examples

• "Set up a $5,000 monthly budget on my subscription."
• “How am I doing against my budgets this month?”

 

Optimize Spend

As cloud environments grow, identifying the highest-impact savings opportunities becomes increasingly challenging. An AI agent can surface appropriate Advisor cost recommendations so you can prioritize actions to improve savings.

Examples

• "Show me any eligible Savings Plans recommendations that would save me at least $200/month.”
• "Show me my reserved instanced utilization for this month."

 

Analyze AKS Workloads

If you’re running AKS workloads on Azure, an AI agent can query AKS cost data by cluster and namespace and compare active and idle capacity.

Examples

• “Show me how much of my AKS spend is idle vs actively used in my current subscription.”
• "Compare costs across my AKS clusters. Which cluster is most expensive this month?"

Make Cost-Aware Azure Decisions

Whether you're evaluating a new deployment, investigating spending changes, tracking budgets, identifying savings opportunities, or analyzing AKS workloads, the Cost Management and Pricing toolsets helps bring financial context directly into Azure workflows. By combining Azure resource information with cost, pricing, budget, and optimization insights, AI agents can help you make more informed decisions without switching between multiple tools and experiences.

What's Included

This release adds both Cost Management and Pricing toolsets to Azure Resource Manager MCP.

• Query and forecast – Explore historical spend, understand cost trends, and project future costs.
• Budgets and alerts – Create, review, and monitor budgets and alerts to help teams stay ahead of overruns.
• Reservations and Savings Plans – Review recommendations and utilization data to identify commitment-based savings opportunities.
• Pricing – Retrieve retail pricing and negotiated price sheet details where available.

Getting Started

Pre-Requisites

• VS Code installed
• Valid Azure account with appropriate permissions
• GitHub Copilot subscription

Installation

1. Install Azure Resource Manager MCP - https://aka.ms/JoinARMMCP 

• VS Code launches automatically
• Click Install under Azure Resource Manager MCP Server
• Sign in with your Azure credentials 
• If you hit any authentication issues, see the Troubleshooting Guide in the Azure Resource Manager MCP repo

2. Add cost headers to Azure Resource Manager MCP configuration file for access to cost tools

• Opt-in per client with x-mcp-toolset headers: CostManagement, Pricing (see below)

     How to add headers per supported client:

     GitHub Copilot Chat in VS Code

• Option 1 (Workspace): configure vscode/mcp.json file in your repo
• Option 2 (User): Edit mcp.json file in User Configuration:
  • Open the Command Palette (Ctrl+Shift+P / Cmd+Shift+P)
  • run MCP: Open User Configuration, and edit the mcp.json it opens

     

 

     

 

 

 

 

 

 

     GitHub Copilot CLI

• Edit ~/.copilot/mcp-config.json with the relevant CostManagement and Pricing headers.

 

3. Save updated configuration file and restart the server

 

 

 

 

 

 

 

 

 

 

 

 

 

4. Start asking cost questions

What's Next?

Azure Cost Management is actively expanding our agentic cost capabilities. Upcoming capabilities:

• Additional tools supported in Cost Management and Pricing toolsets
• Skills that provide best practices and support for advanced workflows for cost scenarios – preview skills here.

Give Feedback

We want to hear from you. Please share your feedback here - https://aka.ms/azurecost/mcptools/give/feedback

 

Resources

- 📖 Documentation  – Complete setup and usage guide for Cost Management and Pricing toolsets in Azure Resource Manager MCP

- 🔗 Feedback  – Share your feedback on Cost Management and Pricing toolsets in Azure Resource Manager MCP

- 🐛 Report Issues  – Report bugs with Azure Resource Manager MCP

- 🛠️ Troubleshooting  – Resolve common issues with Azure Resource Manager MCP