🚀 MCP KQL Server

Name: 🚀 MCP KQL Server
Author: 4R9UN

@4R9UN

🚀 MCP KQL Server について

Kusto and Log Analytics MCP server help you execute a KQL (Kusto Query Language) query within an AI prompt, analyze, and visualize the data.

基本情報

カテゴリ

データと分析

ライセンス

MIT

ランタイム

python

トランスポート

stdio

公開者

4R9UN

設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "mcp-kql-server": {
      "command": "python",
      "args": [
        "-m",
        "mcp_kql_server",
        "--transport",
        "http",
        "--host",
        "127.0.0.1",
        "--port",
        "8000",
        "--http-path",
        "/mcp",
        "--stateless-http"
      ]
    }
  }
}

ツール

ツールは検出されませんでした

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is MCP KQL Server?

MCP KQL Server is an MCP server that transforms natural language questions into optimized KQL queries with intelligent schema discovery, AI-powered caching, and seamless Azure Data Explorer integration. It is for data analysts, developers, and AI agents who need to query Azure Data Explorer using plain English.

How to use MCP KQL Server?

Install with pip install mcp-kql-server, then configure your MCP client (e.g., Claude Desktop, VSCode) to launch the server via python -m mcp_kql_server. The server provides two main tools: execute_kql_query for NL2KQL conversion and direct KQL execution, and kql_schema_memory for schema discovery and cache management.

Key features of MCP KQL Server

Natural Language to KQL (NL2KQL) conversion
Execute raw KQL queries directly
Schema discovery and AI-powered caching
Support for JSON, CSV, and table output formats
Schema-grounded repair of invalid query columns
Cache management and memory statistics

Use cases of MCP KQL Server

Query Azure Data Explorer without writing KQL manually
Explore database schemas and table structures interactively
Generate analysis reports with visualizations from natural language prompts

FAQ from MCP KQL Server

What are the prerequisites for running MCP KQL Server?

Python 3.10 or higher, Azure CLI installed and authenticated (via az login), and access to an Azure Data Explorer cluster.

How do I configure MCP KQL Server for my MCP client?

Add a stdio or HTTP entry to your client's MCP settings file. For Claude Desktop, add {"command": "python", "args": ["-m", "mcp_kql_server"]} to mcp_settings.json. For shared environments, use --transport http.

What transports does MCP KQL Server support?

It supports stdio, HTTP, streamable HTTP, and SSE transports, configurable via the --transport option or the FASTMCP_TRANSPORT environment variable.

How does the server handle authentication?

Authentication is delegated to the Azure CLI. The server can check Azure CLI auth on startup via --auth-on-startup or the MCP_KQL_AUTH_ON_STARTUP environment variable.

Where does MCP KQL Server store its schema cache?

Cached schema data is stored in %APPDATA%\KQL_MCP on Windows or ~/.local/share/KQL_MCP on Linux and macOS.

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