Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Descripción del creador (original en inglés)
MCP gateway: many servers, one policy, lethal-trifecta blocking, PII masking, audit log
Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.
Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.
Elige la app de IA que usas y copia la configuración.
Necesitas
¿Qué app usas?
Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.
Abre Claude Desktop → Settings → Developer → Edit Config y pega esto en claude_desktop_config.json
{
"mcpServers": {
"security-proxy": {
"command": "npx",
"args": [
"-y",
"@guardbee/mcp-security-proxy"
]
}
}
}Ejecuta esto en tu terminal
claude mcp add security-proxy -- npx -y @guardbee/mcp-security-proxyPégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"security-proxy": {
"command": "npx",
"args": [
"-y",
"@guardbee/mcp-security-proxy"
]
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Pégalo en .vscode/mcp.json de tu proyecto
{
"servers": {
"security-proxy": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@guardbee/mcp-security-proxy"
]
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Este se ejecuta en tu computadora, y ChatGPT solo puede conectarse a servidores en internet. Elige otra app.
Tu elección se guarda en una cookie en este dispositivo; no necesitas cuenta.
Esta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.
Se ejecuta en tu computadora; la lista de herramientas aparece en tu app de IA después de instalarlo.
Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 6 nov 2026
El nombre en el registro se verificó con la cuenta de GitHub GuardBee, dueña del repo
Todavía no hemos leído este repo en GitHub
Todavía no hemos leído este repo en GitHub
Este se ejecuta en tu computadora; no hay endpoint en internet
Se ejecuta en tu computadora y usa ajustes locales en su lugar
Se ejecuta en tu computadora; solo podemos leer listas de herramientas de endpoints en internet
Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.
Superó 1 de 1 revisiones básicas aplicables. No hemos leído el código. Antes de agregar una clave o un token, revisa qué acceso pide el servidor y usa una clave que tenga solo los permisos que necesitas.
El registro no indica ninguna clave obligatoria, aunque algunos servidores te piden iniciar sesión la primera vez que los usas.
Se ejecuta en tu computadora. Tu app de IA lo inicia cuando hace falta, y los datos no pasan por los servidores del creador (a menos que el propio servidor llame a un servicio en línea).
El repo de GitHub cambió por última vez –, y la última versión (1.37.1) llegó al registro hace 4 días.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Node.js en tu computadora.
En la misma categoría: Spec Driven Development, Remote Desktop Commander, AI Deprecations
Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.
Cómo leer una tarjeta:★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi
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.
Copiado tal cual del repo del creador. PopNx MCP no lo ha revisado ni lo respalda. Se quitaron HTML, imágenes y scripts. Los enlaces llevan fuera de este sitio.
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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) andSolo se muestra el principio; lee el resto en el repo