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azure-query-mcp

azure-query-mcp

by kapetanios55
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

search_tables

Read-onlyIdempotent

Search for tables in an Azure Log Analytics workspace by name or description substring using its ARM resource ID.

Instructions

List or search tables in a Log Analytics workspace using ARM metadata.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "workspaceResourceId": "<workspaceResourceId>"
    },
    "name": "search_tables"
  }
}

Input Schema

NameRequiredDescriptionDefault
searchNoOptional name or description substring.
workspaceResourceIdYesFull ARM resource ID of the workspace.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A3.8/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true and destructiveHint=false, and the description adds that it uses ARM metadata, clarifying it operates on metadata rather than querying data. However, it does not disclose additional behaviors such as pagination, return format, or search semantics beyond what the schema provides.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, dense sentence that immediately conveys the tool's purpose. No redundant or filler content exists.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple list/search tool with strong annotations and full schema coverage, the description is nearly complete. It lacks explicit details about the return value, but with no output schema and a straightforward use case, the provided information is sufficient.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, with both workspaceResourceId and search having descriptive text. The description itself does not add parameter-level detail, but that is acceptable given the complete schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool lists or searches tables in a Log Analytics workspace, specifying the resource type (tables) and context (Log Analytics workspace). This distinguishes it from siblings like query_workspace (querying data) and describe_table (specific table details).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is implied: if you need to list or search tables, use this tool. However, there is no explicit guidance on when to use this versus alternatives like describe_table for table details or list_workspaces for workspace discovery. No exclusions or alternative suggestions are provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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