原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
PopNx MCP为使用 AI 的人准备的 MCP 服务器 · 用大白话讲清楚

SecHelix

作者:omarmohelal版本 0.3.0i★ –i在你的电脑上运行
注册名称io.github.omarmohelal/sechelix

安装

概览

作者提供的说明(英文原文)

Evidence-first security review of authorized repositories. Read-only, root-confined, no shell.

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

  • 连接方式: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 开发者工具

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
  • 注册中心没有列出需要填写的密钥。

你需要

  • PyPI已安装 Python 的 uv(用于 uvx 命令)

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "sechelix": {
      "command": "uvx",
      "args": [
        "sechelix",
        "mcp",
        "."
      ]
    }
  }
}

在终端中运行这条命令

claude mcp add sechelix -- uvx sechelix mcp .

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "sechelix": {
      "command": "uvx",
      "args": [
        "sechelix",
        "mcp",
        "."
      ]
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "sechelix": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "sechelix",
        "mcp",
        "."
      ]
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上,无需账户。

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

它能做什么

它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月9日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 omarmohelal 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    它在你的电脑上运行;我们只能读取互联网端点的工具列表

与“开发者工具”中的其他服务器比较i

  • 星标数多于此分类中其他 5574 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 5574 个服务器的 37% 更新
  • 基础检查结果等于或优于此分类中其他 5574 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

SecHelix 安全吗?

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。

它在我的电脑上运行还是在云端?

它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(0.3.0)于2个月前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Python (uv)。

有什么可以替代它?

同一分类中有:GitHub, Desktop Commander, Cloudflare MCP

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:↓ 每周下载量i★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

GitHub

Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.

作者:github广泛使用★ 3.4万6天前更新

电脑或云端

Desktop Commander

MCP server for terminal commands, file operations, and process management

作者:wonderwhy-er广泛使用↓ 71万/周★ 1万18天前更新

在你的电脑上运行

Cloudflare MCP

Cloudflare MCP servers

作者:cloudflare广泛使用★ 444614个月前更新

在云端运行✓ mcp.cloudflare.com

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

Most AI security tools try to find more. SecHelix tries to prove itself wrong.

SecHelix

Every candidate finding goes to an independent verifier whose only job is to disprove it. The report shows you what it refuted and why — and returns INCOMPLETE rather than a clean PASS when it could not actually check.

Open source, Apache-2.0, for code you own or are authorized to test. Runs in Claude Code, Codex, Copilot and other Agent Skills-compatible agents; the Python runtime is optional.

It helps a coding agent:

  • map the attack surface and trust boundaries;
  • review only security checks that apply to the project;
  • investigate authentication, authorization, business logic, injection, SSRF, files, supply chain, AI/MCP and other security surfaces;
  • verify important candidates instead of reporting guesses;
  • fix the root cause;
  • add regression proof and retest;
  • return a clear release decision.

See it work in 90 seconds

git clone https://github.com/omarmohelal/SecHelix && cd SecHelix

python examples/expense-api/prove.py

A small multi-tenant API with two candidate issues. One is a real cross-tenant read that a scanner walks past, because the endpoint *does* have an authorization check — it just checks the wrong thing. The other is f-string SQL that every pattern matcher flags and that is not exploitable at all.

Walkthrough, root cause, the two-line fix and the regression proof: [examples/expense-api](examples/expense-api/README.md).

Or take the same test in your browser — ten cases, three of them decoys, no signup: [Can you tell the real bug from the decoy?](https://omarmohelal.github.io/sechelix-challenge/)

Install

Recommended for Agent Skills-compatible coding agents:

npx skills@latest add omarmohelal/SecHelix --skill sechelix

Then open the repository you want to review in your coding agent. The skill installs instructions and data only — no executable code. The optional runtime below is a separate, explicit install.

A compact edition, sechelix-lite, is a single runtime-free review skill (about 200 lines plus five references) for skill directories and hosts where a small context footprint matters. See [docs/distribution/awesome-copilot.md](docs/distribution/awesome-copilot.md).

Use it

Full security audit

Copy this into your agent:

Use SecHelix for a complete authorized security audit of this repository.

Start STATIC and use LOCAL only if it is safe and useful. Map the attack surface and trust boundaries first. Verify important candidates before reporting them. Fix root causes, add regression tests, retest, and give me the final release gate.

Fast security review
Use SecHelix to triage this repository for security issues.

Prioritize authentication, authorization, business logic, secrets, injection, SSRF, file handling, supply chain, dangerous configuration, and AI/MCP surfaces. Return evidence-backed findings and clearly mark anything unproven.

AI-built app launch audit

Use this before launching an AI-generated, agent-generated, rapidly prototyped, or vibe-coded application:

Use SecHelix's AI-Built App Launch Audit on this authorized application.

Evaluate launch checks 01-36 from references/ai-built-app-launch.md. Do not mark PASS without exact code, configuration, policy, test, log, or safe runtime evidence. For every FAIL or security-relevant UNKNOWN, give the realistic failure mode, smallest root-cause fix, and exact safe verification step. After fixes, re-run the failed/unknown checks and produce the normal SecHelix release gate.

The launch profile covers practical pre-release failures around secrets, auth/authz, cross-user data, database/storage permissions, debug exposure, input validation, SQL/NoSQL injection, XSS/CSRF, uploads, traversal, SSRF, password reset, sessions/JWT, CORS, rate limiting, staging, default credentials, webhooks, payments/entitlements, IDOR/BOLA, sensitive logs, and production artifacts.

Review a pull request
Review this PR with SecHelix.

Focus on security changes introduced by the diff, verify important candidates, and tell me whether the PR introduces a verified blocker or known risk.

Fix findings
Use SecHelix Fix Mode on the verified findings.

Fix the root cause, look for variants of the same bug, add security regression tests, and retest the original finding.

More copy-paste workflows: [Command Cookbook](docs/COMMANDS.md).

What should I ask SecHelix to do?

GoalAsk for
Full repository reviewcomplete security audit
Quick first passsecurity triage
AI-built/vibe-coded app before launchAI-Built App Launch Audit
Broken access controlauthorization / IDOR / BOLA audit
Login and sessionsauthentication / session / OAuth audit
Input handlinginjection / XSS / SSRF / files audit
Payments and workflowsbusiness logic / race / idempotency audit
Dependencies and CIsupply chain / CI/CD audit
LLMs, agents and toolsAI / Agent / MCP security audit
A code changePR security review
Existing verified issuesFix Mode
Release decisionrelease gate
Shareable outputsecurity report

You do not need to memorize special slash commands. SecHelix is primarily a skill: tell the coding agent what security job you want done.

How the review works

scope

→ map attack surface → select applicable checks → investigate → independently verify important candidates → fix root cause → add regression proof → retest → report + release gate

A scanner match or model suspicion is treated as a candidate, not automatically as a vulnerability.

A strong finding should show the affected surface, attacker control or security boundary involved, reachability, impact, root cause, safe evidence, the fix, and regression/retest status.

What SecHelix does not claim

  • It is not a certification. PASS means the release-gate rules found no unresolved blocking condition in what was reviewed, not that the software has no vulnerabilities.
  • On real code it found 2 of 12 known CVEs. A blinded run against the vulnerable and patched trees of 12 recent CVEs found 2 cleanly under the pre-registered rule, 3 with hand adjudication, and no finding it marked VERIFIED was one of the known defects (report). Precision is NOT_MEASURED.
  • The model still does the reasoning. SecHelix structures the review and labels unproven claims as unproven rather than dropping them: in that run 92 of 106 findings were marked LIKELY_BUT_UNPROVEN or HYPOTHESIS. It does not make a model see a bug it cannot reason about.
  • Host support varies. Installation is verified for the Claude Code plugin, the Agent Skills CLI, the portable bundle and the curated Copilot CLI plugin; other hosts are documented paths (compatibility).
  • Authorized targets only. It is not an internet scanner and ships no exploit payloads.

Full local runtime: SecHelix + embedded Strix

For the complete local stack, including the exact Strix source revision that SecHelix has compatibility-tested, clone with submodules and run the bootstrap:

git clone --recurse-submodules https://github.com/omarmohelal/SecHelix.git

cd SecHelix bash scripts/bootstrap-full.sh

This materializes Strix under engines/strix inside the SecHelix checkout and installs both projects into one Python 3.12 virtual environment. The source is embedded for reproducible installation, while the SecHelix adapter remains the authorization/evidence boundary. OpenRouter setup and first-run commands are in [docs/full-install.md](docs/full-install.md).

Optional CLI runtime

The Agent Skill works without the Python runtime. The runtime is optional and adds stored runs, coverage tracking, replayable evidence, reports, CI-friendly exit codes, and an MCP adapter.

Install it with:

pipx install sechelix

sechelix doctor

uv tool install sechelix and python -m pip install sechelix are also supported.

Useful CLI commands
CommandWhat it does
sechelix doctorShows available components and reasoning executors
sechelix audit . --executor claude-codeRuns an audit using Claude Code as the reasoning executor
sechelix audit . --executor gemini-cliRuns an audit using Gemini CLI as the reasoning executor
sechelix audit . --resume-from .sechelix/checkpoints/RUN-....json --executor nexusResumes only unfinished nodes after verifying the sealed checkpoint against the same target, scope, graph and input world
sechelix launch-audit . --executor claude-codeRuns evidence-routed AI-built-app launch checks 19-36 without turning “no candidate” into PASS
sechelix runsLists saved runs and checks their integrity
sechelix coverageShows what previous runs did not examine
sechelix reportRenders the latest saved run
sechelix replay Replays a recorded run offline and checks consistency
sechelix mcp .Serves the local MCP adapter over stdio

Example:

sechelix doctor

sechelix audit . --executor claude-code sechelix launch-audit . --executor claude-code sechelix coverage sechelix report --format markdown

sechelix audit . with the default --executor none intentionally does not pretend to analyze code. Reasoning nodes are blocked and the run remains incomplete until a real executor is configured.

Audit and launch-audit runs now write a self-sealed node-boundary checkpoint under .sechelix/checkpoints/ by default. If the process or host dies, pass that file to --resume-from; completed node evidence is kept, remaining nodes can use a different executor/provider, and resume fails closed if the target commit, scope, graph, input world, budget limits, or checkpoint digest changed.

For all CLI flags:

sechelix --help

sechelix audit --help

Advanced runtime guide: [V4 Runtime Quickstart](docs/v4-quickstart.md).

GitHub Action

- uses: omarmohelal/SecHelix@v4.0.0-alpha.7

with: executor: none

Outputs PASS, PASS_WITH_KNOWN_RISK, BLOCKED or INCOMPLETE, writes SARIF for code scanning, and uploads the run as an artifact. The default executor: none deliberately reports INCOMPLETE rather than a green check it did not earn — configure a reasoning executor to get an actual review.

Full reference: [GitHub Action](docs/github-action.md).

MCP adapter

uvx sechelix mcp /path/to/the/repository

Seven tools over a root you choose, no shell, no network. Six only read; sechelix_audit writes only a run workspace inside that root. The root is the security boundary: point it at the repository under review, not at your home directory.

Reference: [MCP adapter](docs/mcp.md).

Execution modes

ModeUse it for
STATICSource, configuration and schema review without dynamic traffic
LOCALSafe dynamic proof against a local app and fixtures
STAGINGExplicitly authorized non-production testing
PRODUCTION_SAFEBounded, non-destructive verification only

Only test systems you own or are explicitly authorized to assess. See [SECURITY.md](SECURITY.md).

只显示了开头部分;其余内容请在仓库中阅读

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