Entra ID SecOps MCP Server
Entra ID SecOps MCP Server
一个 MCP 服务器,将 Microsoft Entra ID 的安全日志公开为可由 AI 代理(Claude Desktop、Cursor 或任何其他 MCP 客户端)执行的工具。
目标:让分析师可以用自然语言提问——“为什么这个账户再也无法登录?”——并在几秒钟内获得基于租户真实数据的答案。
设计原则
Microsoft Graph 的原始响应每个事件包含大约六十个字段。服务器采用激进截断:只有十几个安全指标能够到达模型。这既是成本优化(token 数量减少约 ~35 倍),也是安全控制,因为未列出的字段——其中一些由攻击者控制——永远不会进入上下文。
聚合结果(失败次数、不同 IP、可疑模式)是用 Python 计算的,而不是由模型推断的。
Related MCP server: Microsoft MCP Server for Enterprise
工具
工具 | 说明 | Graph 权限 | 许可证 |
| 账户详情:职位、组、拥有的角色。确定事件的严重性。 |
| — |
| 某个 UPN 的近期登录,包含摘要和可疑模式 |
| P1 |
| 被 Identity Protection 标识为有风险的账户 |
| P2 |
| 单次检测:账户为何存在风险 |
| P2 |
| 管理更改;标记持久化操作 |
| — |
| 有效策略与覆盖缺口 |
| — |
所有工具均为只读:服务器从不修改租户。
建议的调查顺序
get_user_context le compte est-il privilégié ? l'incident est-il grave ?
↓
get_user_signins que s'est-il passé sur l'authentification ?
↓
get_risk_detections qu'a détecté Identity Protection, et pourquoi ?
↓
get_directory_audits l'attaquant a-t-il modifié quelque chose une fois entré ?这一顺序也包含在服务器的 instructions 中,并由 MCP 客户端传递给模型。
快速开始(无需 Azure 租户)
fixture 模式会重放一个演示事件,且不需要租户、许可证或机密。
python -m venv venv
venv/Scripts/activate # Windows ; sur Linux/macOS : source venv/bin/activate
pip install -e ".[dev]"
cp .env.example .env # ENTRA_DATA_SOURCE=fixture est déjà la valeur par défaut
python -m entra_secops_mcp连接到真实租户
在 Entra 门户中创建一个 App Registration。
添加上表中列出的应用权限,然后授予管理员同意。
生成客户端机密。
填写
.env:
AZURE_TENANT_ID=...
AZURE_CLIENT_ID=...
AZURE_CLIENT_SECRET=...
ENTRA_DATA_SOURCE=graph需要许可证。 通过 API 访问登录日志需要 Entra ID P1 许可证, 而 Identity Protection 工具需要 P2。 没有这些许可证时,Graph 返回
403。其他工具无需付费许可证也能运行。 请在开始之前验证租户的许可证:这是经典的阻塞点, 会让人浪费好几天。
安全
代码和 Docker 镜像中都不存在任何机密。它们在启动时通过
--env-file注入。.env通过.gitignore被 git 排除。已推送到仓库的机密必须在 Azure 中撤销,不能只删除文件。日志记录定向到
stderr:在 stdio 传输中,stdout负责传输 JSON-RPC 协议,不能包含任何多余字节。
配置
所有变量都记录在 .env.example 中。
Docker
docker build -t entra-secops-mcp .
docker run -i --rm --env-file .env entra-secops-mcp最终镜像:277 Mo,多阶段构建,以非 root 用户(uid=1000)运行,层中没有机密。
-i 保持标准输入打开——MCP 协议正是通过它传输。不要使用 -t:伪终端会注入颜色代码,从而破坏 JSON 帧。
开发
pytest # 81 tests
ruff check src tests
mypy src # mode strict
pre-commit install # contrôles avant chaque commit
python demo.py # investigation de démonstration状态
工具 | 6 个,全部只读 |
测试 | 81 个,无需 Azure 租户 |
类型检查 |
|
MCP 协议 |
|
容器 | 已通过真实 MCP 客户端验证:启动 2,4 s,工具调用 ~110 ms |
许可证
MIT.
Available Tools
6 toolsget_conditional_access_policiesARead-onlyIdempotent
Liste les politiques d'accès conditionnel du tenant, avec leur état réel d'application.
À utiliser pour expliquer pourquoi une connexion a été bloquée (code 53003), ou pour repérer une faille de couverture : politique désactivée, politique en mode audit seul, ou exclusion qui permet à un compte de contourner un contrôle.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Nombre maximum de politiques. Défaut 25, borné à 100. |
Output Schema
| Name | Required | Description |
|---|---|---|
| notes | No | Observations calculées. |
| disabled | Yes | Politiques désactivées. |
| enforced | Yes | Politiques réellement appliquées. |
| policies | Yes | Politiques du tenant. |
| report_only | Yes | Politiques en mode audit, donc sans effet de blocage. |
| total_policies | Yes | Nombre de politiques retournées. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and non-destructive behavior. The description adds useful behavioral context by promising the 'état réel d'application' and listing the specific coverage-failure states it can reveal. 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two tight sentences: the first announces the action and scope, the second gives concrete use cases. No filler or redundant restatement of schema information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The presence of an output schema covers return structure, the single parameter is fully documented in the schema, and annotations cover behavior. The description supplies the missing contextual layer: why the agent would need this tool and what insights it provides.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% and the single optional limit parameter already has an explicit description with default and maximum. The tool description adds no new param detail, so the default baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Liste') and resource ('politiques d'accès conditionnel du tenant') and adds a distinguishing property ('état réel d'application'). This clearly separates it from the more user-centric sibling tools such as get_user_signins or get_risk_detections.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says when to use it: to explain a blocked connection with error code 53003 or to detect coverage gaps caused by disabled policies, audit-only mode, or exclusions. It does not explicitly name alternatives or say when not to use it, but the use cases are strong and concrete.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_directory_auditsARead-onlyIdempotent
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.
| Name | Required | Description | Default |
|---|---|---|---|
| hours | No | Fenêtre de recherche en heures. Défaut 24, borné à 168. | |
| limit | No | Nombre maximum d'entrées. Défaut 25, borné à 100. | |
| initiated_by | No | UPN de l'auteur des modifications, pour ne retenir que ses actions. Omettre pour balayer toutes les modifications du tenant. |
Output Schema
| Name | Required | Description |
|---|---|---|
| notes | No | Observations calculées. |
| entries | Yes | Entrées, de la plus récente à la plus ancienne. |
| failures | Yes | Opérations en échec. |
| window_hours | Yes | Fenêtre temporelle appliquée, en heures. |
| total_entries | Yes | Nombre d'entrées retournées. |
| sensitive_entries | Yes | Entrées jugées sensibles du point de vue de la sécurité. |
| distinct_initiators | Yes | Auteurs distincts observés. |
TDQS
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.
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.
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.
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.
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.
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.
get_risk_detectionsARead-onlyIdempotent
Récupère les détections de risque unitaires : identifiants divulgués, IP anonymisée, voyage impossible, pulvérisation de mots de passe.
C'est l'outil qui explique POURQUOI un compte est signalé à risque, là où
get_risky_users se contente de dire QUE le compte l'est.
Nécessite une licence Entra ID P2.
| Name | Required | Description | Default |
|---|---|---|---|
| upn | No | UPN à cibler. Omettre pour obtenir les détections de tout le tenant. | |
| hours | No | Fenêtre de recherche en heures. Défaut 24, borné à 168. | |
| limit | No | Nombre maximum de détections. Défaut 25, borné à 100. |
Output Schema
| Name | Required | Description |
|---|---|---|
| notes | No | Observations calculées. |
| detections | Yes | Détections, de la plus récente à la plus ancienne. |
| distinct_types | Yes | Types de détection distincts observés. |
| distinct_users | Yes | UPN distincts concernés. |
| total_detections | Yes | Nombre de détections retournées. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior, so the bar is lower. The description adds valuable context beyond annotations by listing risk detection categories and the Entra ID P2 license requirement. It does not over-explain but gives meaningful operational context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, each earning its place: what the tool returns, how it differs from the sibling, and a hard prerequisite. The content is front-loaded and there is no filler or redundant restatement of the schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the rich annotations, full parameter documentation, and output schema, the description covers everything an agent needs: purpose, scope, alternative routing, and licensing. There are no critical gaps for invoking this tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with each parameter already having a clear description and defaults. The tool description does not add parameter-level meaning, but it does not need to; the schema carries the full burden. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description names a specific verb ('Récupère') and a precise resource ('détections de risque unitaires'), and lists concrete examples (identifiants divulgués, IP anonymisée, voyage impossible, pulvérisation de mots de passe). It also explicitly differentiates itself from get_risky_users by explaining WHY versus THAT, making the tool's purpose unmistakable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It directly positions the tool against get_risky_users: use this one to understand the reason behind a risk flag, while get_risky_users only indicates the flag exists. It also states a key prerequisite, 'Nécessite une licence Entra ID P2', giving the agent an explicit condition for use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_risky_usersARead-onlyIdempotent
Liste les comptes signalés à risque par Entra Identity Protection, du plus risqué au moins risqué.
À utiliser pour obtenir une vue d'ensemble de l'exposition du tenant, ou pour confirmer qu'un compte précis est bien considéré comme compromis.
Nécessite une licence Entra ID P2.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Nombre maximum de comptes retournés. Défaut 25, borné à 100. | |
| only_active | No | Si vrai (défaut), ne retourne que les comptes encore à risque (atRisk, confirmedCompromised) et écarte ceux déjà remédiés ou classés. |
Output Schema
| Name | Required | Description |
|---|---|---|
| notes | No | Observations calculées. |
| users | Yes | Comptes, du plus risqué au moins risqué. |
| high_risk | Yes | Comptes au niveau de risque « high ». |
| active_risk | Yes | Comptes encore à risque (atRisk ou confirmedCompromised). |
| medium_risk | Yes | Comptes au niveau de risque « medium ». |
| total_users | Yes | Nombre de comptes retournés. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover read-only, idempotent, and non-destructive behavior. The description adds useful behavioral context: a required Entra ID P2 license, the risk-ordering behavior, and the scope of accounts returned. 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and front-loaded: main action in the first sentence, use cases in the second, and a prerequisite in the third. Every sentence earns its place with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple two-parameter read-only tool, full schema coverage, and an output schema, the description is complete enough. It covers purpose, ordering, use cases, and licensing without needing to duplicate schema information.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%; both parameters are already well documented in the schema, including defaults and allowed range. The description does not add additional parameter-level meaning beyond the schema, so baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists accounts flagged as risky by Entra Identity Protection, sorted from most to least risky. It is specific about the resource and action, though it does not explicitly name sibling tools for differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says when to use it: to get an overview of tenant exposure or to confirm a specific account is considered compromised. It provides clear usage context, but does not mention exclusions or alternative sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_user_contextARead-onlyIdempotent
Récupère la fiche d'identité d'un compte : poste, département, état, groupes d'appartenance et rôles d'annuaire détenus.
C'est l'outil qui détermine la GRAVITÉ d'un incident. Une connexion suspecte sur un compte sans privilège et sur un compte administrateur global appellent des réponses très différentes.
À appeler systématiquement avant de conclure sur un incident.
| Name | Required | Description | Default |
|---|---|---|---|
| upn | Yes | User Principal Name complet, par exemple « alice@contoso.com ». |
Output Schema
| Name | Required | Description |
|---|---|---|
| notes | No | Observations calculées. |
| groups | No | Groupes d'appartenance. |
| created | No | Date de création du compte. |
| job_title | No | Intitulé de poste. |
| object_id | Yes | Identifiant d'objet Entra. |
| user_type | No | Member ou Guest. |
| department | No | Département. |
| display_name | No | Nom affiché. |
| is_privileged | Yes | Le compte détient-il au moins un rôle à privilèges ? |
| account_enabled | No | Le compte est-il actif ? |
| directory_roles | No | Rôles d'annuaire détenus. |
| privileged_roles | No | Sous-ensemble des rôles à privilèges élevés. |
| user_principal_name | Yes | UPN du compte. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint false, so the safety profile is covered. The description adds the context that this tool is authoritative for severity and that it returns identity attributes, but it doesn't disclose additional behavioral details such as staleness, data-source scope, or potential edge cases. With annotations handling the core safety traits, this is adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the action and resource, then adds two purposeful sentences about severity and systematic use. It is concise and every sentence contributes meaningful guidance. The only minor issue is that the severity phrasing is slightly redundant with the usage instruction, but this is not wasteful.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter tool with a rich output schema and strong annotations, the description is complete: it explains what the tool returns, why it matters, and exactly when to invoke it. Nothing essential is missing for an agent to select and call it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, and the upn parameter already has a clear explanation with an example. The description adds no extra parameter semantics, but the baseline of 3 applies because the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource: 'Récupère la fiche d'identité d'un compte' and enumerates the exact fields returned (poste, département, état, groupes, rôles). It also distinguishes itself from siblings by framing the tool as the one that determines incident severity, so an agent can clearly tell it apart from sign-in or risk-detection tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives strong usage direction: it should be called 'systématiquement avant de conclure sur un incident' and explains why severity depends on account privileges. It lacks explicit when-not-to-use guidance or named alternativatives, so it doesn't quite reach a 5, but the context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_user_signinsARead-onlyIdempotent
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.
| Name | Required | Description | Default |
|---|---|---|---|
| upn | Yes | User Principal Name complet, par exemple « alice@contoso.com ». | |
| hours | No | Fenêtre de recherche en heures. Défaut 24, borné à 168 (7 jours). | |
| limit | No | Nombre maximum d'événements retournés. Défaut 25, borné à 100. |
Output Schema
| Name | Required | Description |
|---|---|---|
| upn | Yes | UPN interrogé. |
| notes | No | Observations calculées automatiquement, à vérifier par l'analyste. |
| events | Yes | Événements, du plus récent au plus ancien. |
| failures | Yes | Nombre d'échecs. |
| successes | Yes | Nombre de connexions réussies. |
| total_events | Yes | Nombre d'événements retournés. |
| window_hours | Yes | Fenêtre temporelle réellement appliquée, en heures. |
| distinct_locations | Yes | Géolocalisations distinctes observées. |
| distinct_ip_addresses | Yes | Adresses IP source distinctes observées. |
TDQS
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.
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.
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.
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.
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.
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.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
6 tool updates
v1.0.0- First observed
get_conditional_access_policies - First observed
get_directory_audits - First observed
get_risk_detections - First observed
get_risky_users - First observed
get_user_context - First observed
get_user_signins
TDQS
Scored across 6 tools
Each tool targets a distinct data source: user identity context, sign-in events, risky user aggregates, individual risk detections, directory audit logs, and conditional access policies. The closely related risky-user and risk-detection tools are explicitly differentiated by scope, so an agent can reliably pick the right one.
All tool names follow a consistent get_<resource> pattern using snake_case: get_user_context, get_user_signins, get_risky_users, get_risk_detections, get_directory_audits, get_conditional_access_policies. The naming convention is uniform and predictable.
Six tools is a tightly scoped set for an Entra ID SecOps investigation server. Each tool covers a necessary aspect of incident investigation without redundancy or bloat.
The tool surface covers the main investigative workflow: identify the user's privilege level, inspect sign-ins, review identity risk, understand specific risk detections, check for malicious directory changes, and evaluate conditional access impacts. No significant operational gap is apparent for the stated SecOps purpose.
Maintenance
Related MCP Connectors
Official Microsoft MCP Server to query Microsoft Entra data using natural language
Find relevant security data from Sentinel data lake for building effective agents. More:aka.ms/s/de
Query your org's data in natural language — read-only MCP access to SQL, NoSQL, files & warehouses.
Ask about your Kodem Security data and act on findings in plain language, with your permissions.
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