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PenTest MCP

PenTest MCP

by anishxagrawal
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

wfuzz

Fuzz web applications by injecting payloads into URLs to uncover hidden parameters, endpoints, and vulnerabilities.

Instructions

Web application fuzzer

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "url": "<url>",
      "session_id": "<session_id>"
    },
    "name": "wfuzz"
  }
}

Input Schema

NameRequiredDescriptionDefault
urlYes
dry_runNoPreview commands/steps without executing the scan
fuzz_paramNoFUZZ
session_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv3.0.0

TDQS

C2/5.0
Behavior2/5

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

With no annotations, the description carries full burden for behavioral disclosure. Merely labeling it a 'fuzzer' implies it sends many requests, potentially destructive, but no specifics on side effects, permissions, rate limits, or output. This is insufficient for safe and correct invocation.

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

Conciseness2/5

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

While extremely concise (4 words), this brevity comes at the cost of essential information. The description is closer to underspecification than efficient conciseness, and lacks any structure or key details.

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

Completeness1/5

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

Given the tool's complexity (fuzzing web apps, 4 parameters including required fields) and the absence of annotations or output schema, the description is completely inadequate. It fails to explain input expectations, behavior, or output, making the tool unusable for an AI agent.

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

Parameters1/5

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

Schema description coverage is very low (25%), with only 'dry_run' having a description. The description 'Web application fuzzer' adds no meaning to the parameters. Critical parameters like 'url', 'fuzz_param', and 'session_id' remain undocumented both in schema and description, leaving the agent unable to use them correctly.

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

Purpose3/5

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

The description 'Web application fuzzer' is minimal but indicates the general category of the tool. However, it lacks specificity about what exactly it fuzzes (e.g., URLs, parameters, headers) and does not differentiate it from sibling tools like ffuf or gobuster, which are also web fuzzers.

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

Usage Guidelines2/5

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

No guidance is provided on when to use wfuzz versus alternatives, nor are there any prerequisites, exclusions, or context for when it is appropriate. The tool exists among many similar fuzzing and scanning tools, making this gap significant.

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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