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Rug Pull Detector

by GuardBeeversion 0.4.2i★ –iRuns on your computer
Registry nameio.github.GuardBee/rug-pull-detector

Install

Overview

Description from the maker (original English)

Baselines an MCP server's tools and detects tool-definition changes after approval

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": {
    "rug-pull-detector": {
      "command": "npx",
      "args": [
        "-y",
        "@guardbee/mcp-rug-pull-detector"
      ]
    }
  }
}

Run this in your terminal

claude mcp add rug-pull-detector -- npx -y @guardbee/mcp-rug-pull-detector

Open in Cursor

Or copy the settings yourself

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

{
  "mcpServers": {
    "rug-pull-detector": {
      "command": "npx",
      "args": [
        "-y",
        "@guardbee/mcp-rug-pull-detector"
      ]
    }
  }
}

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": {
    "rug-pull-detector": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@guardbee/mcp-rug-pull-detector"
      ]
    }
  }
}

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 32531 servers in this category
  • Published to the registry more recently than 86% of the other 32531 servers in this category
  • Basic checks equal to or better than 100% of the other 32531 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 Rug Pull Detector 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 (0.4.2) reached the registry 5 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, Reelsaw

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
Install

Reelsaw

by osbytes

Drive a self-hosted Reelsaw: turn long videos into vertical clips, edit, re-render and export them.

Runs on your computerUpdated 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-rug-pull-detector

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

An MCP (Model Context Protocol) server that connects live to another MCP server and detects an MCP rug pull — a server presenting one tool definition when you approve it, then silently serving a different one later.

Every other scanner in this monorepo reads source code or a config file once. This one is architecturally different: it's an MCP *client*. It spawns the target server (stdio) or opens a session with it (Streamable HTTP), calls the real tools/list RPC, and remembers what it saw — the same trust-on-first-use model an SSH client uses for host keys. A tool's description, input/output schema, or annotations changing between two calls to the exact same server is not something any static analysis of that server's source could ever catch, because the server may not have changed its source at all — it can decide server-side, at request time, what to tell which client.

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 ──► rug-pull-detector ──► (spawns / connects to) ──► Target MCP server

│ │ │ tools/list (real RPC) ▼ .guardbee/tool-baselines/ .json │ 1st contact: baseline_server → store canonical hash per tool every later: check_server → re-fetch, diff against stored hash


The trust-on-first-use model

baseline_server connects once, fetches every tool's {name, description, inputSchema, outputSchema, annotations}, canonicalizes it (deep key-sorted JSON) and stores a SHA-256 hash plus the full snapshot — one JSON file per server under .guardbee/tool-baselines/.

Every check_server also runs the tool-poisoning catalog scan on the live tools/list, including the first time a server is seen and when no baseline is stored yet. A poisoned description does not wait for a second visit.

check_server connects again later — after a version bump, before every session, on a schedule, whatever cadence you choose — and re-fetches the same information. Any tool whose hash no longer matches is reported:

  • critical — an *existing* tool's definition changed (tool_definition_drift). This is the rug pull itself. The finding says exactly which field changed (description / input schema / output schema / annotations) with the before/after description text, because destructiveHint: true → false is just as much a lie as a rewritten description — both change what a caller believes they're authorizing.
  • medium — a *new* tool appeared that wasn't in the baseline (tool_added). Could be a legitimate release. Still worth a look — nothing stops a server introducing its dangerous tool only after the benign ones already earned trust.
  • low — a *previously baselined* tool is no longer offered (tool_removed).

If no baseline exists yet, check_server captures one automatically and reports clean (pass autoBaseline: false / --no-auto-baseline to require an explicit baseline_server call first instead).


Features

  • Real MCP client — not a mock, not a source-code heuristic. Speaks the actual protocol over stdio or Streamable HTTP to whatever server you point it at.
  • Canonical hashing covers name, description, input schema, output schema, and annotations (readOnlyHint, destructiveHint, ...) — a server can't dodge detection by only touching the fields a naive diff would skip.
  • Three ways to specify a target: --stdio="command arg1 arg2", --url= , or --config= --server= (reads an mcpServers-style JSON config directly — the same shape as a Claude Desktop config)
  • SARIF 2.1.0 output — CI/CD integration
  • 28 tests: pure unit tests for hashing/diffing/storage, plus real stdio process-spawning integration tests against a fixture MCP server (not mocked) covering drift, addition, removal, and label isolation. End-to-end verified against ai-code-scanner's own real, already-published MCP server — connected over genuine stdio JSON-RPC, baselined its 4 real tools, and confirmed a second check reports clean.

Quick Start

Claude Desktop / MCP Client
{

"mcpServers": { "guardbee-rug-pull-detector": { "command": "npx", "args": ["-y", "@guardbee/mcp-rug-pull-detector"] } } }

Then ask Claude to baseline a server you're about to add, and to re-check it periodically (e.g. "check this MCP server against its baseline before we use it today").

CLI (CI/CD or scheduled check)
# First contact — do this only after you've reviewed the server's tools

npx @guardbee/mcp-rug-pull-detector baseline --config=claude_desktop_config.json --server=some-third-party-server

Every later run — e.g. a scheduled job, or right before your app starts

npx @guardbee/mcp-rug-pull-detector check --config=claude_desktop_config.json --server=some-third-party-server --fail-on=critical


MCP Tools

ToolDescription
baseline_serverConnects to a server and stores its current tools as the trusted baseline
check_serverConnects to a server and diffs its current tools against the stored baseline
list_baselinesLists every server with a stored baseline

Configuration

No guardbee.yml section — the only persistent state is the baseline directory itself (.guardbee/tool-baselines/ by default, override with --baseline-dir).


Limitations (by design)

  • `--stdio` uses a simple whitespace split, not shell-quote parsing — a command/argument containing spaces will break. Use --config= --server= (reading a real JSON config with a proper args array) for anything beyond a trivial command line.
  • Baseline identity is the `label` you give it (or the command line / URL if you don't), not anything cryptographic about the server itself — renaming how you invoke a server starts a fresh baseline. Keep the label stable.
  • This detects drift in the tool list a server presents, not malicious behavior inside a tool call that was always there. It's the rug-pull defense, not a replacement for mcp-server-auditor or tool-poisoning-scanner — run all three.
  • Connecting to a stdio target means spawning whatever command you give it — the same thing every MCP client already does when you add a server to its config. Only point this at servers you intend to run.

Development

npm run build

npm test # 28 tests


License

MIT — GuardBee

Feedback

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