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Sultan-zd

Entra ID SecOps MCP Server

by Sultan-zd

get_user_signins

Read-onlyIdempotent

Investigate user authentication issues by retrieving recent sign-ins, failures, IPs, and security indicators to detect anomalies or compromise.

Instructions

Récupère les connexions récentes d'un utilisateur pour investiguer un blocage d'authentification, une anomalie géographique ou une compromission.

Retourne les événements réduits à leurs indicateurs de sécurité, plus une synthèse chiffrée (nombre d'échecs, IP distinctes, observations calculées).

Args: upn: User Principal Name complet, par exemple « alice@contoso.com ». hours: Fenêtre de recherche en heures. Défaut 24, maximum 168 (7 jours). limit: Nombre maximum d'événements retournés. Défaut 25, maximum 100.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
upnYesUser Principal Name complet, par exemple « alice@contoso.com ».
hoursNoFenêtre de recherche en heures. Défaut 24, borné à 168 (7 jours).
limitNoNombre maximum d'événements retournés. Défaut 25, borné à 100.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
upnYesUPN interrogé.
notesNoObservations calculées automatiquement, à vérifier par l'analyste.
eventsYesÉvénements, du plus récent au plus ancien.
failuresYesNombre d'échecs.
successesYesNombre de connexions réussies.
total_eventsYesNombre d'événements retournés.
window_hoursYesFenêtre temporelle réellement appliquée, en heures.
distinct_locationsYesGéolocalisations distinctes observées.
distinct_ip_addressesYesAdresses IP source distinctes observées.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.0.0

TDQS

A3.9/5.0
Behavior4/5

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

Beyond the readOnly/idempotent annotations, the description discloses that events are reduced to security indicators and that a quantitative summary (failure counts, distinct IPs, computed observations) is returned. This is useful behavioral context, though it does not discuss rate limits or response edge cases.

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?

The purpose and output behavior are front-loaded and each substantive sentence earns its place. The Args block is somewhat redundant with the input schema, but it is compact and does not make the description overly long.

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 a rich output schema and annotations, the description provides enough context for correct selection and invocation: purpose, use cases, output shape, and parameter defaults. It could be slightly more complete by pointing to a sibling tool for related risk data, but this is not essential.

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?

The schema already documents all three parameters, including defaults and bounds, so coverage is 100%. The description largely repeats this information (upn example, hours default/max, limit default/max) and adds no new parameter semantics beyond the schema.

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?

The description clearly states the tool retrieves recent user sign-ins ('Récupère les connexions récentes d'un utilisateur') for authentication-block, geographic-anomaly, or compromise investigations. It uses a specific verb+resource, but does not explicitly contrast itself with siblings such as get_risk_detections or get_user_context.

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?

It gives concrete investigative scenarios: 'pour investiguer un blocage d'authentification, une anomalie géographique ou une compromission'. There is no explicit when-not-to-use guidance or named alternative, so it stops short of a 5.

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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