Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
作者提供的说明(英文原文)
Scans AI-generated code for invisible Unicode, Trojan Source, and supply-chain threats.
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。
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。
选择你使用的 AI 应用,然后复制设置。
你需要
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": {
"codesafer": {
"command": "npx",
"args": [
"-y",
"cleaner-code"
]
}
}
}在终端中运行这条命令
claude mcp add codesafer -- npx -y cleaner-code粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"codesafer": {
"command": "npx",
"args": [
"-y",
"cleaner-code"
]
}
}
}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。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"codesafer": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"cleaner-code"
]
}
}
}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。
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6日
注册名称已通过 GitHub 账户 goldmembrane 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
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。
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。
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)。
GitHub 仓库最后更新于–,最新版本(1.0.1)于7个月前进入注册中心。
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 Node.js。
同一分类中有:Spec Driven Development, Remote Desktop Commander, SSTracker free youth training
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:★ 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
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Free youth sports drills, practice plans and age-group answers for parents and coaches.
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。
AI code security scanner as a Model Context Protocol (MCP) server.
Detects hidden threats in AI-generated code that traditional linters miss.
Website: codesafer.org · MCP Clients: Claude Code, Cursor, VS Code + Copilot, Cline
AI coding assistants generate code fast — but who's checking it for hidden threats?
Recent supply-chain attacks show that malicious code can hide in ways human reviewers and traditional linters routinely miss:
.cursorrules, CLAUDE.md, and other AI config filespackage.jsoneval + base64, reverse shells, packed payloadsCodeSafer scans for all of these before the code runs on your machine.
CodeSafer runs as a local MCP server. Your AI client (Claude Code, Cursor, etc.) calls its tools when reviewing or generating code, and findings are returned inline.
Hybrid detection:
Nothing leaves your machine. The AI analysis runs locally against a tokenizer server.
| Capability | Details |
|---|---|
| Invisible character detection | 30+ Unicode variants including Zero-Width Space, Mongolian Vowel Separator |
| BiDi / Trojan Source | Full CVE-2021-42574 coverage |
| Homoglyph detection | Cyrillic/Greek/Latin confusables (CVE-2021-42694) |
| Unicode steganography | Glassworm-style whitespace payloads |
| Rules file backdoors | Scans .cursorrules, CLAUDE.md, .claude/, Cursor rules |
| Dependency scanning | Typosquatting + suspicious install scripts in package.json |
| Obfuscation detection | eval + base64, reverse shells, packed payloads |
| AI deep analysis | CodeBERT transformer classifier with confidence scores |
| MCP native | 6 MCP tools, stdio transport |
| Local-first | No code uploaded — runs entirely on your machine |
CodeSafer exposes six tools to your MCP client:
| Tool | Purpose |
|---|---|
scan_file | Scan a single file for hidden malicious code patterns |
scan_directory | Recursively scan a directory across all source files |
scan_rules_file | Scan an AI configuration/rules file for prompt injection and Rules File Backdoor attacks |
check_dependencies | Check package.json for typosquatting, suspicious install scripts, and dependency risks |
ai_analyze | Deep AI analysis using the trained CodeBERT model (classifies chunks as malicious/benign with confidence) |
explain_finding | Get detailed explanation of a specific threat category, with attack scenarios and remediation |
git clone https://github.com/goldmembrane/cleaner-code.git
cd cleaner-code npm install npm run build
Claude Code (~/.claude.json or project .mcp.json):
{
"mcpServers": { "codesafer": { "command": "node", "args": ["/absolute/path/to/cleaner-code/dist/index.js"] } } }
Cursor (.cursor/mcp.json):
{
"mcpServers": { "codesafer": { "command": "node", "args": ["/absolute/path/to/cleaner-code/dist/index.js"] } } }
Restart your client, and CodeSafer tools will appear in the tool picker.
Once configured, ask your AI client things like:
.cursorrules for a rules-file backdoor."*src/auth.ts."*The client will call the appropriate MCP tool and return findings with severity, line numbers, and remediation guidance.
CodeSafer is free to use. Static analysis (scan_file, scan_directory, scan_rules_file, check_dependencies, explain_finding) has no limits.
AI deep analysis (ai_analyze) includes 10 free runs per session. Paid plans for higher AI quotas are available at codesafer.org.
CodeSafer detects threats across 9 categories:
.cursorrules, CLAUDE.md, etc.eval + base64, packed payloads, reverse shellscleaner-code/
├── src/ │ ├── index.ts # MCP server entry point │ ├── api-server.ts # Optional HTTP API server │ ├── types.ts # Scanner interfaces │ ├── utils.ts # File collection, summary formatting │ └── scanner/ │ ├── invisible.ts # Invisible Unicode scanner │ ├── bidi.ts # BiDi / Trojan Source scanner │ ├── homoglyph.ts # Homoglyph scanner │ ├── encoding.ts # Encoding / charset scanner │ ├── obfuscation.ts # Obfuscation pattern scanner │ ├── steganography.ts # Unicode steganography scanner │ ├── rules-backdoor.ts # Rules file backdoor scanner │ ├── dependency.ts # Dependency risk scanner │ └── ai-analyzer.ts # CodeBERT deep analyzer ├── ml/ # ML model assets and tokenizer ├── functions/ # Cloud function deployments ├── deploy/ # Deployment manifests └── web/ # Landing page assets
ISC — see the LICENSE file for details.