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Security Proxy

by GuardBeeversion 1.37.1i★ –iRuns on your computer
Registry nameio.github.GuardBee/security-proxy

Install

Overview

Description from the maker (original English)

MCP gateway: many servers, one policy, lethal-trifecta blocking, PII masking, audit log

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Other

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • The registry lists no key to fill in.

You need

  • npmNode.js installed (for the npx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "security-proxy": {
      "command": "npx",
      "args": [
        "-y",
        "@guardbee/mcp-security-proxy"
      ]
    }
  }
}

Run this in your terminal

claude mcp add security-proxy -- npx -y @guardbee/mcp-security-proxy

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "security-proxy": {
      "command": "npx",
      "args": [
        "-y",
        "@guardbee/mcp-security-proxy"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "security-proxy": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@guardbee/mcp-security-proxy"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account GuardBee, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Otheri

  • More stars than 0% of the other 32380 servers in this category
  • Published to the registry more recently than 89% of the other 32380 servers in this category
  • Basic checks equal to or better than 100% of the other 32380 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Security Proxy safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (1.37.1) reached the registry 4 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, Dechonet MCP

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Spec Driven Development

by formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

Runs on your computer★ 440MITUpdated 14 months ago
Install

Remote Desktop Commander

by desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

Runs in the cloud★ 211Updated yesterday
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Dechonet MCP

by node-man

30 security tools for AI agents: phishing links, exposure maps, DNS, SSL, PQC, history, pivots.

Computer or cloudUpdated today
Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

@guardbee/mcp-security-proxy

🇬🇧 English | 🇹🇷 Türkçe | 🇨🇳 中文 | 🇯🇵 日本語 | 🇰🇷 한국어 | 🇧🇷 Português | 🇪🇸 Español | 🇩🇪 Deutsch

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=1 it sends the server, tool, success, duration and short parameter values such as a file path; longer strings and fields like content, token or password are 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


Features

  • Prompt Injection Protection — 27 rules in English and Turkish; precise ones block, generic phrases only warn
  • Tool-result injection — the same patterns applied to tool results, tagged MCP06:2025. Block mode replaces the result; warn mode prepends a warning
  • Session tool pin — the first 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 call
  • PII Masking — TC Kimlik No, VKN, IBAN, card and phone numbers (checksum-validated), passport, SGK, MERSİS, date of birth, postal and KEP addresses, email, opt-in IP/MAC/plates, 22 provider key formats, private keys and connection strings are masked in responses
  • Block / Warn Mode — each interceptor can independently run in blocking or warning mode
  • Audit Log — configurable log written to console or a file
  • Gateway mode — several MCP servers behind one proxy, one YAML policy (allow / deny / mask / warn)
  • Toxic-flow blocking — tracks the lethal trifecta across servers and blocks the egress call that would complete it
  • LLM API gateway — OpenAI- and Anthropic-compatible endpoints: gateway keys instead of provider keys, PII masking and injection checks on prompts, token and spend budgets, usage and cost in the audit log
  • A2A gateway — Agent2Agent calls between agents go through the gateway: callers authenticate, injection in messages and artifacts is blocked, personal data is masked, push-notification webhooks into private networks are refused, and every call is audited
  • Coding-agent hooks — guardbee-hook applies the same policy to Claude Code's and Cursor's own shell, file and web tools
  • Zero Code Changes — attaches in front of any existing MCP server

Quick Start

npm 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.


Gateway Mode: Several Servers, One Policy

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

  • id: no-deletes match: { tool: "postgres__delete_*" } action: deny # allow | deny | mask | warn | approve
  • match: { tool: "postgres__query", args: { table: "salaries" } } # dotted path → value, strings are globs action: mask mask: { fields: [salary, iban] } # blank these JSON keys
  • match: { label: destructive } action: approve # ask the person first

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

  • Tools and prompts appear as __ .
  • Toxic flow (lethal trifecta): each tool is labeled 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.
  • Rules match on 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.
  • Topics (`topics`, `match.topic`): a rule can name a subject instead of a tool — "nothing about mergers or salaries leaves through this agent". A topic is a list of terms; text is on topic when 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:
  • id: ma terms: [birleşme, "satın alma", "due diligence", acquisition, merger]
  • id: salary terms: [maaş, bordro, payroll, salary] minMatches: 1 rules:
  • { id: no-ma-out, match: { topic: ma, label: egress }, action: deny }
  • { id: contractors, match: { topic: salary, user: "*@contractor.com" }, action: approve }
  • { id: ma-to-llm, match: { topic: ma, tool: "llm:gpt-*" }, action: deny }
- **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.
  • Tool poisoning at `tools/list` (`interceptors.toolPoisoning`, on by default): every definition is scanned before the agent sees it — the description (yours, when you wrote one under 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.
  • Credentials leaving (`interceptors.egressSecrets`, on by default): before an 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 (`interceptors.sampling`, off by default): a server can ask the agent's model for a completion (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

Only the beginning is shown; read the rest in the repo

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