# Azure Data Explorer MCP Server

> Use this tool when you need to authenticate with Azure Data Explorer and execute KQL queries using natural language inputs. It solves problems related to complex query formulation and data exploration by providing a user-friendly interface for querying large datasets. The tool takes natural language queries as input and outputs relevant data results, making it ideal for use cases where users need to quickly extract insights from Azure Data Explorer without requiring extensive KQL knowledge.

Canonical page: https://skillsregistry.net/skills/cheng306-mcp-server  
JSON: https://api.skillsregistry.net/v1/skills/cheng306-mcp-server

## Description

Enables users to authenticate with Azure Data Explorer and execute KQL queries via natural language through the Model Context Protocol.

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** verified
- **Last scanned:** 2026-09-01

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** cloud-infra
- **Updated:** 2026-09-01

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/gvwgjd6eln)
- **Repository:** <https://github.com/cheng306/mcp-server>

## 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": "cheng306-mcp-server"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/cheng306-mcp-server` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/cheng306-mcp-server/pull`

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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