1. Background

Name: 1. Background
Author: nitishsharma25

@nitishsharma25

About 1. Background

An MCP Server for Kusto which is connected to a Chat app with MCP client for answering user queries related to their data in Kusto cluster

Basic information

Config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "mysql-kusto-mcp": {
      "command": "python",
      "args": [
        "main.py",
        "../kusto-mcp-server/main.py"
      ]
    }
  }
}

Tools

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Overview

What is 1. Background?

Background is a chat application that answers Kusto queries in a conversational manner. It uses the MCP Client/Server framework with Azure OpenAI’s LLM to process natural language questions and return query results.

How to use 1. Background?

Set up a Python virtual environment, install dependencies for both kusto-mcp-client and kusto-mcp-server, and create a .env file with Azure OpenAI credentials (API key, endpoint, API version, model). Run az login for Azure CLI authentication, then execute python main.py "../kusto-mcp-server/main.py" from the kusto-mcp-client directory. Enter queries in the terminal and type quit to start a new session.

Key features of 1. Background?

Conversational interface for Kusto queries.
Backend uses MCP Client/Server framework.
Integrates with Azure OpenAI’s language models.
Authenticates via Azure CLI.
Terminal-based chat with session management.

Use cases of 1. Background?

Data analysts exploring Kusto clusters with natural language.
Developers embedding Kusto query capabilities into chat tools.
Teams needing quick, conversational access to Azure Data Explorer.

FAQ from 1. Background

What are the prerequisites?

Python, pip, and Azure OpenAI service parameters (API key, endpoint, API version, model). You also need Azure CLI for Kusto authentication.

How do I authenticate with Kusto?

The app uses Azure CLI authentication. Run az login before starting the chat session.

How do I start a new chat session?

Type quit in the terminal to end the current session, then re‑run the client script.

Comments

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