能力标签
安全调查工具
🔌
MCP工具

安全调查工具

基于 Python · 让 AI 助手直接操作你的系统与工具
英文名:security-investigator
⭐ 204 Stars 🍴 52 Forks 💻 Python 📄 MIT 🏷 AI 7.5分
7.5AI 综合评分
安全调查自动化
✦ AI Skill Hub 推荐

安全调查工具 是 AI Skill Hub 本期精选MCP工具之一。综合评分 7.5 分,整体质量较高。我们推荐使用将其纳入你的 AI 工具库,帮助提升工作效率。

📚 深度解析

安全调查工具 是一款基于 MCP(Model Context Protocol)标准协议的 AI 工具扩展。MCP 协议由 Anthropic 开发并开源,旨在建立 AI 模型与外部工具之间的标准化通信接口,目前已被 Claude Desktop、Claude Code、Cursor 等主流 AI 工具采纳。

通过安装 安全调查工具,你的 AI 助手将获得额外的工具调用能力,可以用自然语言直接操控该工具的功能,无需学习复杂的命令行语法。MCP 工具的核心价值在于"一次配置,永久增强"——配置完成后,每次与 AI 对话时都可以无缝调用这些工具。

在技术实现上,MCP 工具通过标准的 JSON-RPC 协议与 AI 客户端通信,工具的功能以"工具列表"的形式暴露给 AI 模型,AI 可以按需调用。安全调查工具 提供了结构化的工具调用接口,使 AI 模型能够精确地理解和使用每个功能点,显著降低 AI 在工具使用上的错误率。

与传统的 API 集成相比,MCP 工具的优势在于无需编写代码——用户只需在配置文件中添加几行 JSON,即可让 AI 获得全新能力。AI Skill Hub 将 安全调查工具 评为 AI 评分 7.5 分,属于同类工具中的优质选择。

📋 工具概览

安全调查工具 是一款遵循 MCP(Model Context Protocol)标准协议的 AI 工具扩展。通过 MCP 协议,它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务,实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用,都可以通过自然语言在 AI 对话中直接触发,极大提升生产效率。

GitHub Stars
⭐ 204
开发语言
Python
支持平台
Windows / macOS / Linux
维护状态
轻量级项目,按需更新
开源协议
MIT
AI 综合评分
7.5 分
工具类型
MCP工具
Forks
52

📖 中文文档

以下内容由 AI Skill Hub 根据项目信息自动整理,如需查看完整原始文档请访问底部「原始来源」。

安全调查工具 是一款遵循 MCP(Model Context Protocol)标准协议的 AI 工具扩展。通过 MCP 协议,它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务,实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用,都可以通过自然语言在 AI 对话中直接触发,极大提升生产效率。

📌 核心特色
  • 通过标准 MCP 协议与 Claude、Cursor 等主流 AI 客户端深度集成
  • 提供结构化工具调用接口,显著降低 AI 集成复杂度
  • 支持 Claude Desktop 和 Claude Code 无缝接入,开箱即用
  • 可与其他 MCP 工具组合叠加,构建完整 AI 工作站
  • 轻量无侵入设计,不影响现有系统架构
🎯 主要使用场景
  • 在 Claude Desktop 对话中直接调用本地工具,实现 AI 与系统的深度联动
  • 通过自然语言驱动复杂的多步骤自动化任务,代替繁琐手动操作
  • 将多个 MCP 工具组合使用,构建个人专属 AI 工作站
以下安装命令基于项目开发语言和类型自动生成,实际以官方 README 为准。
安装命令
# 方式一:通过 Claude Code CLI 一键安装
claude skill install https://github.com/SCStelz/security-investigator

# 方式二:手动配置 claude_desktop_config.json
{
  "mcpServers": {
    "------": {
      "command": "npx",
      "args": ["-y", "security-investigator"]
    }
  }
}

# 配置文件位置
# macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
# Windows: %APPDATA%/Claude/claude_desktop_config.json
📋 安装步骤说明
  1. 确认已安装 Node.js(v18 或以上版本)
  2. 打开 Claude Desktop 或 Claude Code 的 MCP 配置文件
  3. 按「交给 Agent 安装 → Claude Desktop」标签中的 JSON 配置填入 mcpServers 字段
  4. 保存配置文件并重启 Claude 客户端
  5. 重启后,在对话中即可使用本工具
以下用法示例由 AI Skill Hub 整理,涵盖最常见的使用场景。
常用命令 / 代码示例
# 安装后在 Claude 对话中直接使用
# 示例:
用户: 请帮我用 安全调查工具 执行以下任务...
Claude: [自动调用 安全调查工具 MCP 工具处理请求]

# 查看可用工具列表
# 在 Claude 中输入:"列出所有可用的 MCP 工具"
以下配置示例基于典型使用场景生成,具体参数请参照官方文档调整。
配置示例
// claude_desktop_config.json 配置示例
{
  "mcpServers": {
    "______": {
      "command": "npx",
      "args": ["-y", "security-investigator"],
      "env": {
        // "API_KEY": "your-api-key-here"
      }
    }
  }
}

// 保存后重启 Claude Desktop 生效
📑 README 深度解析 真实文档 完整度 75/100 查看 GitHub 原文 →
以下内容由系统直接从 GitHub README 解析整理,保留代码块、表格与列表结构。

🔒 Security Investigation Automation System

Comprehensive, automated security investigations powered by Microsoft Sentinel, Defender XDR, Graph API, and threat intelligence — with 25 specialized Agent Skills

📺 Video Walkthrough: See this project in action — Watch on YouTube (starts at the Security Investigator demo). Covers the end-to-end workflow: natural language investigations, MCP server integration, KQL query execution, threat intelligence enrichment, and automated report generation.

An investigation automation framework that combines GitHub Copilot, VS Code Agent Skills, and Model Context Protocol (MCP) servers to enable natural language security investigations. Ask questions like "Investigate this user for the last 7 days" or "Is this IP malicious?" and get comprehensive analysis with KQL queries, threat intelligence correlation, and professional reports.

Architecture Overview

┌────────────────────────────────────────────────────────────────────┐
│                     GitHub Copilot (VS Code)                       │
├────────────────────────────────────────────────────────────────────┤
│                  .github/copilot-instructions.md                   │
│            (Skill detection, universal patterns, routing)          │
├────────────────────────────────────────────────────────────────────┤
│                     .github/skills/*.md                            │
│       (25 specialized workflows with KQL, risk assessment)         │
├────────────────────────────────────────────────────────────────────┤
│                     MCP Servers (Platform)                         │
│  ┌─────────────┐  ┌──────────────┐  ┌───────────────────────────┐  │
│  │ Sentinel    │  │ Graph API    │  │ Sentinel Triage (XDR)     │  │
│  │ Data Lake   │  │ (Identity)   │  │ (Advanced Hunting)        │  │
│  └─────────────┘  └──────────────┘  └───────────────────────────┘  │
│  ┌─────────────┐  ┌──────────────┐  ┌───────────────────────────┐  │
│  │ KQL Search  │  │ Microsoft    │  │ Azure MCP Server          │  │
│  │ (Schema)    │  │ Learn (Docs) │  │ (ARM + Monitor)           │  │
│  └─────────────┘  └──────────────┘  └───────────────────────────┘  │
│  ┌─────────────┐                                                   │
│  │ Sentinel    │                                                   │
│  │ Graph (Rel) │                                                   │
│  └─────────────┘                                                   │
├────────────────────────────────────────────────────────────────────┤
│               MCP Apps (Local Custom Servers)                      │
│  ┌─────────────┐  ┌──────────────┐  ┌───────────────────────────┐  │
│  │ Geomap      │  │ Heatmap      │  │ Incident Comment          │  │
│  │ (Attack Map)│  │ (Patterns)   │  │ (Sentinel Integration)    │  │
│  └─────────────┘  └──────────────┘  └───────────────────────────┘  │
├────────────────────────────────────────────────────────────────────┤
│                      Python Utilities                              │
│ generate_report_from_json.py  │  enrich_ips.py  │  report_generator│
└────────────────────────────────────────────────────────────────────┘

Key Components: - 25 Agent Skills — Modular investigation workflows for incidents, users, devices, IoCs, authentication, scope drift (SPN/User/Device), MCP monitoring, exposure management, AI agent posture, app registration posture, identity posture, data security analysis, email threat posture, MITRE ATT&CK coverage, ingestion analysis, detection authoring, threat pulse scanning, SVG dashboards, and more - 7 MCP Server Integrations — Sentinel Data Lake, Graph API, Defender XDR Triage, KQL Search, Microsoft Learn, Azure MCP Server, Sentinel Graph (private preview) - 3 Local MCP Apps — Interactive heatmaps, geographic attack maps, incident commenting - Python Utilities — HTML report generation with IP enrichment (geolocation, VPN detection, abuse scores, Shodan port/service/CVE intelligence)

---

pip install -r requirements.txt # Without hash verification

Prerequisites

RequirementDetails
**VS Code**Version 1.99+ recommended (Agent mode + MCP support).
**GitHub Copilot**Active subscription — [Copilot Pro+](https://github.com/features/copilot), Business, or Enterprise. Agent mode must be enabled.
**Python 3.8+**For IP enrichment utility and report generation. [Download](https://www.python.org/downloads/)
**Azure CLI**Required for Azure MCP Server (underlying auth) and sentinel-ingestion-report skill (az monitor log-analytics query for all KQL queries, az rest for analytic rule inventory, az monitor log-analytics workspace table list for tier classification). [Install](https://aka.ms/installazurecli). Authenticate: az login --tenant <tenant_id>, then az account set --subscription <subscription_id>. Requires **Log Analytics Reader** (KQL queries + table list) and **Microsoft Sentinel Reader** (analytic rule inventory) on the workspace.
**log-analytics CLI extension**Required by the sentinel-ingestion-report skill for az monitor log-analytics query (all KQL queries in Phases 1-5). Install: az extension add --name log-analytics. Verify: az extension list --query "[?name=='log-analytics']".
**PowerShell 7.0+**Required for sentinel-ingestion-report skill (parallel query execution via ForEach-Object -Parallel). [Install](https://learn.microsoft.com/en-us/powershell/scripting/install/installing-powershell). Verify: $PSVersionTable.PSVersion.
**Node.js 18+**Required for KQL Search MCP (npx) and building local MCP Apps. [Download](https://nodejs.org/) or install via winget install OpenJS.NodeJS.LTS (Windows) / brew install node (macOS).
**Microsoft Sentinel**Log Analytics workspace with data. You'll need the workspace GUID and tenant ID.
**Entra ID Permissions**If you can query Sentinel in the Azure Portal, you likely have sufficient access. The **Graph MCP server** requires a [one-time tenant provisioning](https://learn.microsoft.com/en-us/graph/mcp-server/get-started?tabs=http%2Cvscode) by an admin. See [MCP Server Setup](#-mcp-server-setup) for detailed per-server requirements.
**Microsoft.Graph PowerShell**Required for detection-authoring skill (CustomDetection.ReadWrite.All — create/update/delete custom detection rules via Graph API). Also used by sentinel-ingestion-report skill for rule inventory (CustomDetection.Read.All — read-only, degrades gracefully if not installed). Install-Module Microsoft.Graph.Authentication -Scope CurrentUser.
**GitHub PAT**public_repo scope — [Create one here](https://github.com/settings/tokens/new). Used by KQL Search MCP.

1. Install Dependencies

Verify prerequisites:

python --version   # Requires 3.8+
node --version     # Requires 18+ (needed for KQL Search MCP)
az --version       # Azure CLI (needed for Azure MCP Server, ingestion report skill)
pwsh --version     # Requires 7.0+ (needed for sentinel-ingestion-report skill)

If Node.js is missing: Download or run winget install OpenJS.NodeJS.LTS (Windows) / brew install node (macOS). If Azure CLI is missing: Install, then az login --tenant <tenant_id> and az account set --subscription <subscription_id>. If the log-analytics extension is missing: az extension add --name log-analytics (required for sentinel-ingestion-report skill).

Set up Python environment:

python -m venv .venv
.\.venv\Scripts\Activate.ps1
pip install -r requirements.txt

Dependencies

pip install -r requirements.txt

Core packages: requests (HTTP client for enrichment APIs), python-dateutil (date parsing for KQL time ranges).

---

🚀 Setup

4. Build MCP Apps (Optional — Visualization Skills)

PowerShell (Windows):

cd mcp-apps/sentinel-geomap-server; npm install; npm run build; cd ../..
cd mcp-apps/sentinel-heatmap-server; npm install; npm run build; cd ../..
cd mcp-apps/sentinel-incident-comment; npm install; npm run build; cd ../..

Bash (macOS/Linux):

cd mcp-apps/sentinel-geomap-server && npm install && npm run build && cd ../..
cd mcp-apps/sentinel-heatmap-server && npm install && npm run build && cd ../..
cd mcp-apps/sentinel-incident-comment && npm install && npm run build && cd ../..

The sentinel-incident-comment MCP App requires an Azure Logic App backend. See mcp-apps/sentinel-incident-comment/README.md for setup. Based on stefanpems/mcp-add-comment-to-sentinel-incident.

---

🔌 MCP Server Setup

The system uses several Model Context Protocol (MCP) servers. All are pre-configured in .vscode/mcp.json.template — copy it to .vscode/mcp.json to get started (see Step 3 above). The sections below document permissions, tools, and installation guides for each server.

1. Install the Entra Beta PowerShell module (v1.0.13+)

Install-Module Microsoft.Entra.Beta -Force -AllowClobber

Verify Setup

Open Copilot Chat (Ctrl+Shift+I) in Agent mode and try these prompts:

TestPrompt to type in Copilot Chat
Sentinel Data LakeList my Sentinel workspaces
Microsoft GraphLook up my user profile in Graph
Sentinel TriageList recent security incidents
KQL SearchWhat columns does the SigninLogs table have?
Microsoft LearnSearch Microsoft docs for KQL query language
All skillsWhat investigation skills do you have access to?

If any server fails, check the MCP Servers panel in VS Code (click the {} icon in the bottom status bar) to verify each server shows a green connected status.

---

Quick Start (TL;DR)

```powershell

2. Set up Python environment

python -m venv .venv .venv\Scripts\Activate.ps1 # Windows

source .venv/bin/activate # macOS/Linux

pip install --require-hashes -r requirements.lock # Hash-verified (recommended)

3. Configure environment

copy config.json.template config.json

Edit config.json → add your Sentinel workspace ID, tenant ID

copy .env.template .env

Edit .env → add your API tokens (ipinfo, AbuseIPDB, vpnapi, Shodan)

4. Configure MCP servers

copy .vscode\mcp.json.template .vscode\mcp.json

All platform servers are pre-configured — just needs a GitHub PAT on first use

2. Configure Environment

Copy config.json.template to config.json and fill in your workspace details:

{
  "sentinel_workspace_id": "YOUR_WORKSPACE_ID_HERE",
  "tenant_id": "YOUR_TENANT_ID_HERE",
  "subscription_id": "YOUR_SUBSCRIPTION_ID_HERE",
  "azure_mcp": {
    "resource_group": "YOUR_LOG_ANALYTICS_RESOURCE_GROUP",
    "workspace_name": "YOUR_LOG_ANALYTICS_WORKSPACE_NAME",
    "tenant": "YOUR_TENANT_ID_HERE",
    "subscription": "YOUR_SUBSCRIPTION_ID_HERE"
  },
  "output_dir": "reports"
}
SettingRequiredDescription
sentinel_workspace_idYesMicrosoft Sentinel (Log Analytics) workspace GUID
tenant_idYesEntra ID (Azure AD) tenant ID for your Sentinel workspace
subscription_idYesAzure subscription ID containing the Sentinel workspace
azure_mcp.*YesAzure MCP Server parameters — resource group, workspace name, tenant, subscription. Required to avoid cross-tenant auth errors.
output_dirNoDirectory for HTML reports (default: reports)

API Tokens (.env file)

API tokens for IP enrichment are stored in a .env file (gitignored) rather than config.json for security. Copy the template and add your keys:

```powershell copy .env.template .env

Edit .env with your token values

dotenv IPINFO_TOKEN=your_token_here ABUSEIPDB_TOKEN=your_token_here VPNAPI_TOKEN=your_token_here SHODAN_TOKEN=your_token_here ```

These are auto-loaded by enrich_ips.py via python-dotenv — no manual sourcing needed.

TokenRequiredDescription
IPINFO_TOKENRecommended[ipinfo.io](https://ipinfo.io/) API token — geolocation, ASN, org. Free: 1K/day; token: 50K/month; paid plans include VPN detection
ABUSEIPDB_TOKENRecommended[AbuseIPDB](https://www.abuseipdb.com/) API token — IP reputation scoring (0-100 confidence). Free: 1K/day
VPNAPI_TOKENOptional[vpnapi.io](https://vpnapi.io/) API token — VPN/proxy/Tor detection. Not needed if ipinfo.io is on a paid plan
SHODAN_TOKENOptional[Shodan](https://account.shodan.io/) API key — open ports, services, CVEs, OS detection, tags. Free InternetDB fallback if no key or credits exhausted

3. Configure MCP Servers

Copy the MCP server template (all platform servers + 3 optional MCP Apps are pre-configured):

copy .vscode/mcp.json.template .vscode/mcp.json

The template includes inline documentation for each server. On first use, VS Code will prompt for: - Entra ID login — browser-based auth for Sentinel Data Lake, Graph, Triage, and Sentinel Graph servers - GitHub PAT — for KQL Search MCP (schema intelligence and query discovery). Needs public_repo scope.

See MCP Server Setup below for per-server permissions and installation guides.

⚙️ Configuration Details

🧠 (Optional) Persistent Tenant Context

GitHub Copilot Chat in VS Code provides agents with a memory tool — a built-in filesystem (/memories/) for persisting notes across conversations. Copilot already uses this internally; you can extend it with tenant-specific context (known infrastructure IPs, validated personnel, false-positive patterns, lab automation signatures) so investigations don't repeatedly mis-classify documented activity as 🔴 critical.

Two memory tiers are relevant:

TierPathAuto-loaded?Use for
**User memory**/memories/*.md✅ Yes (~200 lines)Short trigger rules ("when you see tenant X, read repo file Y")
**Repo memory**/memories/repo/*.md❌ Filenames onlyRich tenant context (IPs, personnel, FP patterns) — pulled in by trigger rules
The memory tool is an internal agent capability — VS Code does not publish a dedicated docs page for it. Closest related concepts are custom instructions and Agent Skills, which serve different purposes (always-applied conventions and specialized workflows, respectively).

This workspace ships with:

  • Templates in notes/memory/examples/ — copy and adapt for your tenant (one user-tier example, two repo-tier examples)
  • Sync script scripts/sync-repo-memory.ps1 — backs up workspace-scoped (repo) memory from VS Code AppData into the workspace folder, surviving VS Code reinstall and workspace rename. Any cloud sync attached to your workspace (OneDrive, Dropbox, iCloud, etc.) then mirrors the backup across machines. Defaults to one-way export (ToBackup); restore mode (FromBackup) requires -Force because it writes into Copilot's trusted memory store.
  • Setup guide notes/memory/README.md — full walkthrough, sync usage, security model, and the trigger-rule pattern that makes Copilot actually consult repo memory

Quickstart: Open a template from notes/memory/examples/, then ask Copilot in chat to "create this as a memory file at /memories/..., replacing placeholders with my tenant values." Copilot uses its memory tool to write it directly — no AppData path navigation needed.

⚠️ Memory = trusted input. Anything in notes/memory/repo/ becomes authoritative instructions for Copilot in every future chat (with MCP tool access to Sentinel, Graph, Azure). Review diffs from forks/PRs before restoring, never paste secrets, and if your workspace is cloud-synced, confirm the destination is acceptable for security context. See notes/memory/README.md for the full threat model.

---

API Rate Limits (IP Enrichment)

ProviderFree TierWith Token
**ipinfo.io**1,000/day (geo, org, ASN)50,000/month; paid plans include VPN detection
**AbuseIPDB**1,000/day10,000/day ($20/month)
**vpnapi.io**1,000/month10,000/month ($9.99/month)
**Shodan**InternetDB (unlimited, ports/vulns/tags)$49 one-time membership: 100 queries/month (adds services, banners, SSL, OS)

Token priority: If ipinfo_token is a paid plan, VPN detection is included and vpnapi_token is optional. Shodan uses the full API when a paid key is available; on 403/429 it automatically falls back to the free InternetDB.

IP enrichment happens during report generation (not data collection), so you can re-generate reports without re-querying Sentinel/Graph.

Threat Intelligence APIs

  • ipinfo.io — IP geolocation, ISP/ASN identification, hosting provider detection
  • vpnapi.io — VPN, proxy, Tor exit node, and relay detection
  • AbuseIPDB — Community-sourced IP abuse scoring and recent attack reports
  • Shodan — Open port enumeration, service/banner detection, CVE identification, infrastructure tagging

1. Clone and open in VS Code

git clone https://github.com/SCStelz/security-investigator.git code security-investigator

3. Register the MCP Server and grant permissions to VS Code

Grant-EntraBetaMCPServerPermission -ApplicationName VisualStudioCode ```

This only needs to be done once per tenant. After provisioning, all users in the tenant can use the Graph MCP server by signing in with their own account.

Permissions (delegated, per-user): - User.Read.All — user profiles and authentication methods - UserAuthenticationMethod.Read.All — MFA methods - Device.Read.All — device compliance and enrollment - IdentityRiskEvent.Read.All — Identity Protection risk detections

🛠️ Troubleshooting

IssueSolution
**"No anomalies found"**Signinlogs_Anomalies_KQL_CL table doesn't exist or has no data. See user-investigation skill docs. Wait 24h for initial population.
**"IP enrichment failed"**ipinfo.io rate limits (1K/day free). Add token to config.json for 50K/month.
**"MCP server not available"**Check VS Code MCP server config. Verify authentication tokens are valid.
**"User ID not found" (Graph)**Verify UPN is correct. Check Graph permissions: User.Read.All.
**"Sentinel query timeout"**Reduce date range. Add \| take 10 to limit results.
**Report generation fails**Validate JSON: python -m json.tool temp/investigation_*.json. Check required fields.
**SecurityIncident returns 0 results**Use BOTH targetUPN and targetUserId (Object ID). Some incidents use Object ID.
**Risky sign-ins 404**Must use /beta endpoint, not /v1.0.
🇨🇳 中文文档镜像 AI 翻译 2026-06-09
英文原文章节由系统翻译为中文摘要,便于快速理解。完整原文见上方 "📑 README 深度解析"。
📌 简介

安全调查自动化系统是一种综合的、自动化的安全调查系统,基于 Microsoft Sentinel、Defender XDR、Graph API 和威胁智能等技术,拥有 25 个专业的技能。

📋 环境依赖

本项目需要以下环境依赖和系统要求:Python 3.8+、Node.js 18+、Azure CLI 和 PowerShell 7.0+。

🛠 安装步骤(Docker/pip/源码)

安装步骤包括:安装依赖项、配置环境、设置 MCP 服务器和部署可视化技能。

🚀 使用教程

使用本项目的快速入门包括:安装依赖项、配置环境、设置 MCP 服务器和部署可视化技能。

⚙️ 配置说明(含 MCP / env)

配置说明包括:设置 MCP 服务器、配置环境变量和设置关键参数。

🔌 API 说明

API/接口说明包括:IP 地理位置、ISP/ASN 识别、VPN 检测等威胁智能 API。

❓ FAQ 摘要

常见问题包括:解决“无异常发现”和“IP enrich failed”的问题。

🎯 aiskill88 AI 点评 A 级 2026-06-04

高质量的自动化安全调查工具

📚 实用指南(长尾问题)
适合谁
  • 需要让 Claude / Cursor 操作本地工具的 AI 工程师
  • 构建多智能体协作系统的 Agent 开发者
最佳实践
  • 配置 MCP 服务器时建议使用 stdio 传输 + JSON-RPC,避免暴露公网
  • Agent 任务先做 dry-run 验证工具调用链,再开启自主执行
常见错误
  • API key 直接提交到 git 仓库(请用 .env 并加入 .gitignore)
  • MCP 配置路径拼错或权限不足,重启 Claude Desktop 才生效
  • Python 依赖冲突:建议用 venv / uv 隔离环境
部署方案
  • CLI:直接 npm install -g / pip install,命令行调用
  • 云端托管:可放在 Vercel / Railway / Fly.io 等 PaaS 平台
相关搜索
security-investigator 中文教程security-investigator 安装报错怎么办security-investigator MCP 配置security-investigator Agent 工作流security-investigator 与同类工具对比security-investigator 最佳实践security-investigator 适合谁用

⚡ 核心功能

👥 适合谁
  • 需要让 Claude / Cursor 操作本地工具的 AI 工程师
  • 构建多智能体协作系统的 Agent 开发者
⭐ 最佳实践
  • 配置 MCP 服务器时建议使用 stdio 传输 + JSON-RPC,避免暴露公网
  • Agent 任务先做 dry-run 验证工具调用链,再开启自主执行
⚠️ 常见错误
  • API key 直接提交到 git 仓库(请用 .env 并加入 .gitignore)
  • MCP 配置路径拼错或权限不足,重启 Claude Desktop 才生效
  • Python 依赖冲突:建议用 venv / uv 隔离环境

👥 适合人群

Claude Desktop / Claude Code 用户AI 工具开发者需要扩展 AI 能力的专业人士自动化工程师

🎯 使用场景

  • 在 Claude Desktop 对话中直接调用本地工具,实现 AI 与系统的深度联动
  • 通过自然语言驱动复杂的多步骤自动化任务,代替繁琐手动操作
  • 将多个 MCP 工具组合使用,构建个人专属 AI 工作站

⚖️ 优点与不足

✅ 优点
  • +MIT 协议,可免费商用
  • +标准化 MCP 协议,生态互联性强
  • +与 Claude 官方生态无缝对接
  • +即插即用,配置简单快捷
⚠️ 不足
  • 依赖 Claude 客户端,非 Claude 用户无法使用
  • MCP 协议仍在持续演进,接口可能变更
  • 需要一定的配置步骤
⚠️ 使用须知

AI Skill Hub 为第三方内容聚合平台,本页面信息基于公开数据整理,不对工具功能和质量作任何法律背书。

建议在沙箱或测试环境中充分验证后,再部署至生产环境,并做好必要的安全评估。

📄 License 说明

✅ MIT 协议 — 最宽松的开源协议之一,可自由商用、修改、分发,仅需保留版权声明。

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📰 相关 AI 新闻
🍿 AI 圈相关吃瓜
🗺️ 相关解决方案
🧩 你可能还需要
基于当前 Skill 的能力图谱,自动补全的工具组合

❓ 常见问题 FAQ

security-investigator 是一款Python开发的AI辅助工具。开源MCP工具:Automated security investigation tool using Microsoft MCP Servers, GitHub Copilo。⭐204 · Python 主要应用场景包括:安全事件调查。
💡 AI Skill Hub 点评

经综合评估,安全调查工具 在MCP工具赛道中表现稳健,质量良好。如果你已有明确的使用需求,可以直接上手体验;如果还在评估阶段,建议对比同类工具后再做决策。

⬇️ 获取与下载
⬇ 下载源码 ZIP

✅ MIT 协议 · 可免费商用 · 直接从 aiskill88 服务器下载,无需跳转 GitHub

📚 深入学习 安全调查工具
查看分步骤安装教程和完整使用指南,快速上手这款工具
🌐 原始信息
原始名称 security-investigator
原始描述 开源MCP工具:Automated security investigation tool using Microsoft MCP Servers, GitHub Copilo。⭐204 · Python
Topics 安全调查自动化
GitHub https://github.com/SCStelz/security-investigator
License MIT
语言 Python
🔗 原始来源
🐙 GitHub 仓库  https://github.com/SCStelz/security-investigator

收录时间:2026-06-04 · 更新时间:2026-06-06 · License:MIT · AI Skill Hub 不对第三方内容的准确性作法律背书。