Kusto and Log Analytics MCP server help you execute a KQL (Kusto Query Language) query within an AI prompt, analyze, and visualize the data.
Config is the same across clients — only the file and path differ.
{
"mcpServers": {
"mcp-kql-server": {
"args": [
"-m",
"mcp_kql_server"
],
"type": "stdio",
"command": "python"
}
}
}Are you the author?
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AI-Powered KQL Query Execution with Natural Language to KQL (NL2KQL) Conversion and Execution
Run this in your terminal to verify the server starts. Then let us know if it worked — your result helps other developers.
uvx 'mcp-kql-server' 2>&1 | head -1 && echo "✓ Server started successfully"
After testing, let us know if it worked:
Five weighted categories — click any category to see the underlying evidence.
No known CVEs.
Checked mcp-kql-server against OSV.dev.
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mcp-name: io.github.4R9UN/mcp-kql-server
AI-Powered KQL Query Execution with Natural Language to KQL (NL2KQL) Conversion and Execution
A Model Context Protocol (MCP) server that transforms natural language questions into optimized KQL queries with intelligent schema discovery, AI-powered caching, and seamless Azure Data Explorer integration. Simply ask questions in plain English and get instant, accurate KQL queries with context-aware results.
Latest Version: v2.1.4 - Canonical schema type normalization for sharper NL2KQL accuracy, credential redaction in logs, leaner dependencies, and a single-source package version.
Watch a quick demo of the MCP KQL Server in action:
execute_kql_query:
kql_schema_memory:
graph TD
A[👤 User Submits KQL Query] --> B{🔍 Query Validation}
B -->|❌ Invalid| C[📝 Syntax Error Response]
B -->|✅ Valid| D[🧠 Load Schema Context]
D --> E{💾 Schema Cache Available?}
E -->|✅ Yes| F[⚡ Load from Memory]
E -->|❌ No| G[🔍 Discover Schema]
F --> H[🎯 Execute Quer
... [View full README on GitHub](https://github.com/4R9UN/mcp-kql-server#readme)