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entraadm-mcp

by shigechika
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

signin_by_ip

Investigate sign-in activity from a specific IP address: identify successful and failed logins per account, with timestamps, for security triage after suspicious IP detection.

Instructions

Every sign-in from one source IP: who got in from it, who was tried, and when.

The follow-up to a spray_suspects or shared_ips hit: Graph can filter sign-ins on ipAddress server-side, so this is one cheap query, not a log walk. users summarises the IP per account (successes, failures, first/last seen, up to 50 accounts) over every row fetched; events lists the newest top entries that match result ("all" by default, or "success" / "failure"), each carrying the account name and the same AADSTS annotation as signin_logs. capped=true means the page budget or the deadline ran out before the window was fully read; events_truncated=true means more matching rows were read than top returns (the users summary still counts them).

Read-only (AuditLog.Read.All application permission, or -- for azure-cli auth -- the Reports Reader directory role).

Args: ip: The source IPv4 or IPv6 address, exactly as the sign-in log shows it. hours: How far back to look, clamped to [1, 720] (30 days). result: "all" (default), "success", or "failure" -- which events to list. top: Maximum events to return, clamped to [1, 500]. max_pages: Page budget (default: ENTRAADM_MAX_PAGES_DEFAULT).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ipYes
topNo
hoursNo
resultNoall
max_pagesNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.1.0

TDQS

A4.7/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and does so thoroughly: it declares read-only status, states the exact permission/role required (AuditLog.Read.All application permission or Reports Reader role), and explains operational signals (capped, events_truncated) beyond anything in structured fields.

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

Conciseness4/5

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

Front-loaded with purpose and behavior before the Args block. The prose is dense and slightly wordy in places (e.g., the elaborated users/events description), but each sentence conveys usable information rather than filler.

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

Completeness5/5

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

With no annotations and no output schema, the description still explains return structure (users summary with up to 50 accounts, events with AADSTS annotations, capped/events_truncated flags), permissions, and all parameter semantics. Nothing an agent needs to invoke it correctly is missing.

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

Parameters5/5

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

Schema description coverage is 0%, so the description must compensate, and it documents all five parameters: ip format, hours clamp [1,720], result enum values, top clamp [1,500], and max_pages default. This is exactly the compensation required when the schema is silent.

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 opening sentence states a specific verb+resource+scope: 'Every sign-in from one source IP: who got in from it, who was tried, and when.' It also implicitly separates itself from signin_logs by framing the results as IP-scoped, and names upstream triggers (spray_suspects, shared_ips).

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

Usage Guidelines4/5

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

Clearly positions itself as 'the follow-up to a spray_suspects or shared_ips hit' and explains that Graph filters on ipAddress server-side, making it a cheap query rather than a log walk. It does not explicitly name signin_logs as the alternative to use for non-IP-scoped queries, so the when-not is only implied.

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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