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Generate and run KQL from natural language with schema discovery for Azure Data Explorer.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "MCP KQL Server" MCP server from askskill: Run: claude mcp add 'io-github-4r9un-mcp-kql-server' -- npx -y mcp-kql-server
Connect to Azure Data Explorer, discover available databases and table schemas, then convert the request 'active users by region in the last 30 days' into KQL and execute it. Summarize the results in a table.
Provides the generated KQL, execution results in a table, and a brief explanation of key fields and metrics.
Inspect the log-related schemas and identify services with a spike in error rate over the last 24 hours. Generate KQL to summarize anomaly counts, error types, and affected services by hour, and highlight the most likely incident window.
Outputs troubleshooting KQL, hourly anomaly summaries, and a brief assessment of the peak incident period.
I’m not familiar with this ADX cluster’s data model. First list the databases, tables, and fields most relevant to retention, sessions, and events, then provide three KQL query examples suitable for product analytics.
Returns a relevant schema inventory plus ready-to-use KQL examples with explanations of their purposes.
No documentation provided
Check the source repo for usage and examples.
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