pab1it0/adx-mcp-server
by Various
A Model Context Protocol (MCP) server that enables AI assistants to query and analyze Azure Data Explorer databases through standardized interfaces.
MCP
pab1it0/adx-mcp-server
Added 1 June 2026
Overview
An MCP server that allows AI assistants to query and analyze Azure Data Explorer databases. It uses the Model Context Protocol to provide a standardized interface for data exploration and querying.
Best for
Best for
Developers building AI assistants that need to query Azure Data Explorer databases
Use cases
- Query Azure Data Explorer databases from AI assistants
- Perform natural language analysis on large-scale telemetry data
- Integrate Azure Data Explorer with MCP-compatible AI tools
How to use
Install
uv pip install -e . Tools exposed
execute_querylist_tablesget_table_schemasample_table_dataget_table_detailsADX_CLUSTER_URLADX_DATABASEAZURE_TENANT_IDAZURE_CLIENT_IDADX_TOKEN_FILE_PATHADX_MCP_SERVER_TRANSPORTADX_MCP_BIND_HOSTADX_MCP_BIND_PORTLOG_LEVEL
Tested with
Claude Desktop
Notes
An MCP server that allows AI assistants to query and analyze Azure Data Explorer databases. It uses the Model Context Protocol to provide a standardized interface for data exploration and querying.
55 stars on GitHub. Last updated 2026-03-25. Licensed MIT.
Use cases
- Query Azure Data Explorer databases from AI assistants
- Perform natural language analysis on large-scale telemetry data
- Integrate Azure Data Explorer with MCP-compatible AI tools
Pros
- Open source with a Python codebase
- Provides a standardized MCP interface for Azure Data Explorer
- Enables AI assistants to directly query and analyze data
Cons
- Small community with only 55 GitHub stars
- Requires familiarity with both Azure Data Explorer and MCP
- May not be extensively tested for production workloads
Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.
Pros
- Open source with a Python codebase
- Provides a standardized MCP interface for Azure Data Explorer
- Enables AI assistants to directly query and analyze data
Cons
- Small community with only 55 GitHub stars
- Requires familiarity with both Azure Data Explorer and MCP
- May not be extensively tested for production workloads
Pairs with
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