Secops Toolkit MCP
Local, no-API-key MCP server with seven defensive SecOps tools for AI agents: extract IOCs (IPs, URLs, domains, hashes, CVE IDs) from text with defang/refang, hash strings, estimate password entropy, and run CIDR/subnet checks. Built on FastMCP with no outbound network calls.
README
SecOps Toolkit MCP
A small, dependency-light Model Context Protocol server that gives an AI assistant a set of defensive security helpers for working with logs, threat-intel notes, and network data — all running locally, with no API keys and no outbound network calls.
Built with FastMCP.
Tools
| Tool | What it does |
|---|---|
extract_iocs |
Pull IPs, URLs, domains, MD5/SHA1/SHA256 hashes, and CVE IDs out of free-form text. Handles defanged input (1.2.3[.]4, hxxp://). |
defang_ioc |
Make an indicator safe to paste: 1.2.3.4 → 1.2.3[.]4. |
refang_ioc |
Reverse a defanged indicator back to its real form. |
hash_text |
Hash a string with md5 / sha1 / sha256 / sha512. |
password_entropy |
Estimate password strength in bits of entropy. |
cidr_info |
Describe a CIDR network: netmask, host range, size, privacy. |
ip_in_cidr |
Check whether an IP falls inside a CIDR range. |
These are defensive / analysis utilities — parsing, hashing, and network math. They don't scan, attack, or reach out to any host.
Install & run
Requires Python 3.11+ and uv.
git clone https://github.com/glatinone/secops-toolkit-mcp.git
cd secops-toolkit-mcp
uv sync
uv run secops-toolkit-mcp # starts the server over stdio
Use it from an MCP client
Add this to your client's MCP config (e.g. Claude Desktop's
claude_desktop_config.json). Point --directory at where you cloned the repo:
{
"mcpServers": {
"secops-toolkit": {
"command": "uv",
"args": ["run", "--directory", "/absolute/path/to/secops-toolkit-mcp", "secops-toolkit-mcp"]
}
}
}
Then ask your assistant things like "extract the IOCs from this alert" or "is 10.0.4.20 inside 10.0.0.0/16?" and it will call these tools.
Development
uv sync # install deps (incl. dev)
uv run pytest # run the test suite
The logic lives in core.py as plain,
testable functions; server.py is a thin
layer that exposes them as MCP tools.
License
MIT — see LICENSE.
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。