# azure-latency-mcp

> Use this tool when you need to measure TCP connection latency to Azure blob storage endpoints across regions. It solves problems related to optimizing performance by identifying the best region for data storage and transfer, and provides inputs such as region selection and outputs like latency measurements. Ideal for use cases where low-latency data access is critical, such as real-time applications or global content delivery.

Canonical page: https://skillsregistry.net/skills/emrgcl-azure-region-advisor  
JSON: https://api.skillsregistry.net/v1/skills/emrgcl-azure-region-advisor

## Description

Measures TCP connection latency to Azure blob storage endpoints across regions, enabling AI-assisted region selection for optimal performance.

## Trust

- **Trust score (0–1):** 0.68
- **Verification tier:** scanned
- **Last scanned:** 2026-08-31

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** cloud-infra
- **Updated:** 2026-08-31

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/ynenfxiip0)
- **Repository:** <https://github.com/emrgcl/Azure-Region-Advisor>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "emrgcl-azure-region-advisor"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/emrgcl-azure-region-advisor` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/emrgcl-azure-region-advisor/pull`

---
SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt