Azure Skills Plugin is an agent plugin that packages Azure-specific guidance with MCP server configurations for carrying out Azure work. Coding agents use it to plan, deploy, troubleshoot, monitor, govern, and optimize Azure applications and services. The catalogue entries are the plugin's skills, instructions, and execution integrations.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/microsoft/azure-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/mcp/microsoft/azure-skills/azure-cost-azure-resource-manager-mcp)<a href="https://agentmods.dev/mcp/microsoft/azure-skills/azure-cost-azure-resource-manager-mcp"><img src="https://agentmods.dev/badge/mcp/microsoft/azure-skills/azure-cost-azure-resource-manager-mcp/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/mcp/microsoft/azure-skills/azure-cost-azure-resource-manager-mcp"><img src="https://agentmods.dev/badge/mcp/microsoft/azure-skills/azure-cost-azure-resource-manager-mcp.svg" alt="Reviewed on agentmods" width="80" height="20"></a>Grade A, and why
azure-resource-manager-mcp scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to azure-resource-manager-mcp — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
{
"azure-resource-manager-mcp": {
"type": "http",
"url": "https://mcp.management.azure.com",
"headers": {
"x-mcp-toolset": "CostManagement"
}
}
}What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 3d ago First seen · 9 lines scan A c812c2094c52
azure-resource-manager-mcp is an MCP server published in the GitHub repository microsoft/azure-skills (1,503 stars, last pushed 2d ago), licensed MIT. Its token cost is not measured: an MCP server costs its tool schemas, not its config file. A static security scan graded it A with 0 findings. It is 100% identical to azure-resource-manager-mcp, differing in 0 lines, and is treated as a copy.
Other mcp servers, from other repositories
k8s-mcp-server
MCP server "k8s-mcp-server" as configured in VersusControl/devops-ai-guidelines. Launched with ${workspaceFolder}/code/04/bin/k8s-mcp-server.
dataproc
MCP server "dataproc", hosted remotely at dataproc-$gcpregion.googleapis.com, as configured in gemini-cli-extensions/data-agent-kit-starter-pack. Needs 1 environment variable to run.
robotmcp
Modular MCP server with Streamable HTTP, optional OAuth 2.1, Supabase auth, Cloudflare tunnel, and creator-only access control. Runs locally from the robotmcp.server Python package. Needs 4 environment variables to run.
mcp-pve
Manage Proxmox VE through AI assistants. Runs locally from the @samik081/mcp-pve npm package. Needs 3 environment variables to run.
ssh-licco
SSH Model Context Protocol Server - Enable SSH functionality for AI models. Runs locally from the ssh-licco Python package. Needs 4 environment variables to run.
terraform
MCP server "terraform" as configured in aws-samples/sample-agentic-chatbot-accelerator. Runs in Docker (hashicorp/terraform-mcp-server:0.5.2).