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)
MCP gateway: many servers, one policy, lethal-trifecta blocking, PII masking, audit log
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": {
"security-proxy": {
"command": "npx",
"args": [
"-y",
"@guardbee/mcp-security-proxy"
]
}
}
}在终端中运行这条命令
claude mcp add security-proxy -- npx -y @guardbee/mcp-security-proxy粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"security-proxy": {
"command": "npx",
"args": [
"-y",
"@guardbee/mcp-security-proxy"
]
}
}
}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": {
"security-proxy": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@guardbee/mcp-security-proxy"
]
}
}
}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 GuardBee 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(1.37.1)于4天前进入注册中心。
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, AI Deprecations
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.
AI model shutdown dates, replacements, change feed and webhook alerts for 8 providers.
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。
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A transparent security layer that sits in front of any MCP server. Blocks prompt injection attacks, masks PII in responses, and writes every request to an immutable audit log.
Telemetry is off by default. With
GUARDBEE_TELEMETRY=1it sends the server, tool, success, duration and short parameter values such as a file path; longer strings and fields likecontent,tokenorpasswordare replaced with a placeholder. See@guardbee/mcp-telemetry.
Claude ──► MCP Security Proxy ──► Any MCP Server
│ ├─ Prompt injection detection (27 rules, EN + TR) ├─ PII + secret masking (TC, VKN, IBAN, card, phone, 22 key formats) ├─ Block or warn mode ├─ Toxic-flow (lethal trifecta) blocking └─ Hash-chained audit log
tools/list is pinned. A later description or schema change is a rug pull (MCP03:2025). Block mode keeps serving the pinned definition and refuses the drifted callguardbee-hook applies the same policy to Claude Code's and Cursor's own shell, file and web toolsnpm install -g @guardbee/mcp-security-proxy
Add to claude_desktop_config.json:
{
"mcpServers": { "secure-filesystem": { "command": "npx", "args": [ "-y", "@guardbee/mcp-security-proxy", "--", "npx", "-y", "@modelcontextprotocol/server-filesystem", "/tmp" ] } } }
The proxy launches whatever comes after
--as the target MCP server.
Put every MCP server behind one proxy with a guardbee-proxy.yaml. init does the move for you:
npx -y @guardbee/mcp-security-proxy@^1 init --client claude-desktop # or cursor, claude-code, --file ./mcp.json
It moves each stdio server into ~/.guardbee/guardbee-proxy.yaml (mode 0600), backs up the client config and points it at the proxy. HTTP servers stay as they are and are reported, because they would bypass the policy. --dry-run prints both files without writing. Or by hand:
{
"mcpServers": { "guardbee": { "command": "npx", "args": ["-y", "@guardbee/mcp-security-proxy@^1", "--config", "/path/to/guardbee-proxy.yaml"] } } }
version: 1
upstreams: github: command: npx args: ["-y", "@modelcontextprotocol/server-github"] env: { GITHUB_PERSONAL_ACCESS_TOKEN: "${GITHUB_TOKEN}" } # read from the environment postgres: command: npx args: ["-y", "@guardbee/mcp-db-gateway"]
labels: # override the heuristic labels github__get_issue: [untrusted] github__create_pull_request: [egress]
tools: # what the agent sees (globs on ) hide: ["*delete_*"] descriptions: github__create_issue: "Create an issue in acme/* repositories only."
rules: # first match wins
taint: mode: strict # strict | approve | warn | off basis: capability # capability | data — data: block only egress calls that carry sensitive data
interceptors: anomaly: # off unless set; limits per session, sliding window enabled: true action: warn # warn | block callBurst: { count: 60, windowSeconds: 60 }
audit: sink: file filePath: ./guardbee-audit.jsonl
__ .untrusted, sensitive, egress or destructive (name/description heuristics, overridable under labels). Once a session has read untrusted content (an untrusted tool or any resource) and sensitive data (a sensitive tool or any PII in a result), an egress call is blocked in strict mode and only logged in warn mode. The check spans servers: an issue read from GitHub plus a customer record from a CRM blocks a webhook on a third server.tool (glob), upstream, label, session (clean | tainted) and args. mask forces PII masking for that tool even when masking is off, and mask.fields also blanks the named JSON keys in text and structuredContent. A rule's allow does not skip the toxic-flow check; relabel the tool instead.minMatches (default 1) different terms appear. Matching folds case and Turkish letters (BİRLEŞME = birlesme), and a term may take a suffix (maaş finds maaşları, satın alma finds satın almayı); quote a term to match the whole word only ('"AI"'). The rule is checked on the call's arguments, and again on what comes back — the tool result, a resource, a prompt — so a subject that only shows up in the answer is caught too: deny withholds it, mask forces PII masking and mask.fields, warn logs, approve asks (once: not again for the answer of a call it already approved). In the LLM API gateway topic rules apply to the whole prompt, with tool: llm: ; approve refuses there, since an API call has no one to ask. topics:
- **Tool exposure (`tools`):** `expose` is an allowlist of globs on the name the agent sees (absent: every tool), and `hide` removes tools after it. A hidden tool is left out of `tools/list`, so the model never reads its description (a smaller poisoning surface and fewer tokens), and a call to it is refused and counts toward `anomaly.repeatedBlocks`. `descriptions` replaces a tool's description with one you wrote; drift detection keeps watching the server's own. Unlike a `deny` rule, which refuses at call time, hiding takes the tool out of the agent's view.
tools.descriptions), parameter descriptions and enum values in the input schema, and the read-only annotation. It catches instructions aimed at the model ( , "do not tell the user", "ignore previous instructions"), cross-tool shadowing ("when using the X tool, always…"), requests to read .ssh/.env, hidden zero-width, bidi and ANSI characters, words with Cyrillic or Greek lookalikes, and a readOnlyHint that the description contradicts. In block mode (default; follows promptInjection.action when unset) a tool with a critical or high finding is left out of the list and its calls are refused; medium findings (encoded blobs) only warn. Each finding is logged once as ruleId: poisoning: . The rules are the ones @guardbee/mcp-tool-poisoning-scanner uses, now shared through guard-core.egress tool runs, the arguments it would actually receive are checked for credentials — provider keys (AWS, GitHub, OpenAI, Anthropic, Stripe, Slack, …), private keys and connection strings with a password; the same fixed-format rules PII masking uses, never the broad keyword ones. Data taint only knows what this session's tools returned; this also catches a key the model got from the prompt, a file or its own context. block (default; follows promptInjection.action when unset) refuses the call, warn logs it; the audit event has the credential masked either way. A PII token stays a token for an egress tool unless piiMasking.detokenizeForEgress, so only then is its value checked. allowTools exempts tools by glob (a deploy tool that takes a DB URL, say). Personal data is left to PII masking and taint.sampling/createMessage) — and a malicious one can use that to smuggle instructions to the model or pull data out. Off, the proxy does not offer sampling to servers at all. On, a request is answered only while one of that server's tool calls is running, by the session that made the call (two sessions calling the same server at once: refused, since it could belong to either); includeContext is forced to none, so a server never gets the conversation; maxTokens is capped (default 1024) and只显示了开头部分;其余内容请在仓库中阅读