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azure-query-mcp

azure-query-mcp

by kapetanios55
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

entity_timeline

Read-onlyIdempotent

Builds a cross-source activity timeline for a user, IP, or host from sign-ins, audit, Office, endpoint, firewall, and alert data, skipping tables not ingested.

Instructions

Build a cross-source activity timeline for one account (UPN), IP address or host: sign-ins, audit events, Office activity, endpoint telemetry, firewall logs and alerts. Tables that are not ingested are skipped automatically.

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": {
      "workspaceId": "<workspaceId>",
      "entityType": "<entityType>",
      "entity": "<entity>"
    },
    "name": "entity_timeline"
  }
}

Input Schema

NameRequiredDescriptionDefault
entityYesUPN (user@domain), IPv4/IPv6 address, or hostname/FQDN.
timespanNoISO 8601 duration back from now (P7D, PT12H), or an interval: start/end (2026-10-01T00:00:00Z/2026-10-02T00:00:00Z) or start/duration (2026-10-01T08:00:00Z/PT6H). Times need Z or an offset. Default P7D.P7D
maxEventsNoMaximum timeline events returned (per-source totals are always complete).
entityTypeYesKind of entity.
workspaceIdYesWorkspace ID (GUID) or the workspace's full ARM resource ID; list_workspaces returns both.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.5.0

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already establish read-only, idempotent, non-destructive, open-world behavior, so the safety profile is covered. The description adds genuinely useful behavior beyond that: missing tables are silently skipped, meaning results can be partially sourced without erroring — an important caveat for interpreting output.

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?

Two sentences, front-loaded with the verb and scope, followed by the one operational caveat that matters. No filler and nothing buried.

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?

With no output schema, the description does tell the agent what content the timeline contains and that per-source aggregation is involved. It stops short of describing the returned event shape or ordering, which an agent consuming the result would benefit from, but the essentials for calling it correctly are present.

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%, including entity formats, timespan syntax variants, the maxEvents cap and the meaning of workspaceId, so the schema does the heavy lifting. The description's mention of UPN/IP/host restates what the entity parameter already documents, adding no new syntax or semantics.

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

Purpose4/5

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

States a specific verb and resource — 'Build a cross-source activity timeline' — and enumerates the source families it fuses (sign-ins, audit, Office, endpoint, firewall, alerts). It does not explicitly contrast itself with siblings like query_workspace or run_hunting_query, so the distinction is inferable rather than stated.

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 by the single-entity scoping ('one account (UPN), IP address or host'), which tells the agent this is an entity-centric pivot. There is no explicit when-to-use versus raw-query siblings such as run_hunting_query or query_workspace, and no stated prerequisites or exclusions.

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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