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Sultan-zd

Entra ID SecOps MCP Server

by Sultan-zd

get_directory_audits

Read-onlyIdempotent

Inspect recent Entra ID directory changes after a suspicious sign-in to identify unauthorized modifications, config drift, and persistence or privilege-elevation actions.

Instructions

Récupère les modifications administratives récentes de l'annuaire, afin d'identifier une dérive de configuration ou un changement non autorisé.

Signale automatiquement les opérations à valeur de persistance ou d'élévation de privilèges : attribution de rôle, ajout d'un secret applicatif, enrôlement d'une méthode MFA, modification d'une politique d'accès conditionnel.

À utiliser après avoir constaté une connexion suspecte, pour déterminer ce que l'attaquant a fait une fois entré.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
hoursNoFenêtre de recherche en heures. Défaut 24, borné à 168.
limitNoNombre maximum d'entrées. Défaut 25, borné à 100.
initiated_byNoUPN de l'auteur des modifications, pour ne retenir que ses actions. Omettre pour balayer toutes les modifications du tenant.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
notesNoObservations calculées.
entriesYesEntrées, de la plus récente à la plus ancienne.
failuresYesOpérations en échec.
window_hoursYesFenêtre temporelle appliquée, en heures.
total_entriesYesNombre d'entrées retournées.
sensitive_entriesYesEntrées jugées sensibles du point de vue de la sécurité.
distinct_initiatorsYesAuteurs distincts observés.

Schema Changelog

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

  1. First observedv1.0.0

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare the tool safe (readOnlyHint, idempotentHint, destructiveHint=false). The description adds meaningful behavioral context—that the tool automatically flags persistence or privilege-escalation operations such as role assignments, app secret additions, MFA enrollment, and conditional access changes. No contradiction with annotations.

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 compact and front-loaded: the first sentence states the core action and purpose, the second adds high-value behavioral specifics, and the third gives usage guidance. Every sentence earns its place with no redundancy or 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?

For a tool with only three optional parameters, a rich annotation set, and an output schema, the description is complete. It covers what the tool does, what it highlights, and when to use it. Nothing critical is missing for an agent to select and invoke it correctly.

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%, so the input schema already documents hours, limit, and initiated_by with defaults and bounds. The description does not add further parameter-level meaning, which matches the baseline of 3 for high 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 opens with a specific verb and resource: 'Récupère les modifications administratives récentes de l'annuaire'. It also states the investigative purpose (identify configuration drift or unauthorized change), which clearly distinguishes it from sibling tools that focus on user context, sign-ins, or risk detections.

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?

The final sentence gives an explicit trigger condition: 'À utiliser après avoir constaté une connexion suspecte, pour déterminer ce que l'attaquant a fait une fois entré.' This provides clear context for when to invoke the tool. However, it does not explicitly name alternatives or state when not to use it, 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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