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@guardbee/mcp-security-proxy

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rug_pull_detector__check_server

Connect to an MCP server and compare its current tools/list response with a stored baseline to detect rug pulls: silent changes in descriptions, schemas, or annotations.

Instructions

Connect to an MCP server and compare its current tools/list response against the stored baseline. A tool whose description, schema, or annotations changed since baseline is a 'rug pull' — approved once, silently different now. If no baseline exists yet, one is captured automatically (set autoBaseline=false to require an explicit baseline_server call first).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cwdNoWorking directory for the spawned process
envNoExtra environment variables for the spawned process
urlNoURL of a Streamable HTTP MCP server (alternative to command/args)
argsNoArguments for the stdio command
labelNoStable identifier for this server, used to look up its baseline. Defaults to the command line or URL.
commandNoCommand to spawn for a stdio MCP server (e.g. "npx")
autoBaselineNoAutomatically capture a baseline if none exists yet (default: true)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.1.1

TDQS

A4/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden. It usefully discloses the autoBaseline default and the exact comparison dimensions (description, schema, annotations), but never mentions that it spawns a process / makes a network connection, nor any permission or side-effect profile for a tool that executes external commands.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three tight sentences: purpose first, then the definition of the failure mode, then the edge-case behavior. Every sentence earns its place and the most important routing caveat is saved for last.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool that spawns or connects to arbitrary servers with no output schema, the description explains the operation and the autoBaseline branch well. It would be stronger if it hinted at what a result looks like (changed vs. unchanged report), since no output schema exists to cover that.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all 7 parameters including autoBaseline. The description reinforces autoBaseline's default and effect, but adds no syntax or meaning beyond the schema for command/args/url/env/cwd/label.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (connect and compare) and resource (current tools/list response vs. stored baseline), and defines the key domain term 'rug pull' inline. It distinguishes itself from the sibling rug_pull_detector__baseline_server by naming it in the autoBaseline caveat.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Clear about when it applies (checking a server's tools against its baseline) and names the alternative flow (autoBaseline=false + baseline_server call) for the no-baseline case. It stops short of stating when a caller should prefer this over list_baselines or when detection is inappropriate.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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