adx-mcp-server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| ADX_DATABASE | Yes | The name of your Azure Data Explorer database | |
| ADX_CLUSTER_URL | Yes | The URL of your Azure Data Explorer cluster |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
| logging | {} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| extensions | {
"io.modelcontextprotocol/ui": {}
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| execute_queryB | Executes a Kusto Query Language (KQL) query against the configured Azure Data Explorer database and returns the results as a list of dictionaries. |
| list_tablesA | Retrieves a list of all tables available in the configured Azure Data Explorer database, including their names, folders, and database associations. |
| get_table_schemaB | Retrieves the schema information for a specified table in the Azure Data Explorer database, including column names, data types, and other schema-related metadata. |
| sample_table_dataB | Retrieves a random sample of rows from the specified table in the Azure Data Explorer database. The sample_size parameter controls how many rows to return (default: 10). |
| get_table_detailsC | Retrieves table details including TotalRowCount, HotExtentSize |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 5 tools
Each tool targets a distinct purpose: listing tables, retrieving schema, retrieving details, sampling data, and executing arbitrary queries. No overlap and clear boundaries between tools.
All tool names follow a consistent verb_noun pattern (e.g., list_tables, get_table_schema, execute_query) using snake_case, making them predictable and easy to interpret.
Five tools is well-scoped for a read-only Azure Data Explorer query server, covering essential operations like listing, schema retrieval, details, sampling, and querying without unnecessary clutter.
The tool set provides a solid foundation for querying and metadata retrieval. Missing are data modification or ingestion tools, but for a query-focused server this is acceptable, though a bit more (e.g., table statistics) could enhance completeness.