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DansPK

Kali MCP

by DansPK

wfuzz

Fuzz URLs, POST data, headers, cookies, and authentication to discover parameters, brute-force logins, and test header injection.

Instructions

Feature-rich web application brute-forcer. Fuzzes URLs, POST data, headers, cookies, and authentication. Use for parameter discovery, login brute-force, header injection testing, and custom fuzzing scenarios. More flexible than ffuf for complex fuzzing (multi-point injection, encoders, auth handling). Output: requests with their response codes, line/word/char counts.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
optsNoAdditional wfuzz options (e.g. '-d "user=FUZZ&pass=FUZZ"' for POST data fuzzing)
targetYesTarget URL with FUZZ keyword (e.g. 'http://example.com/FUZZ')
wordlistYesPath to wordlist file
filter_codeNoHTTP codes to HIDE from output (e.g. '404,500'). Helps reduce noise.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior3/5

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

With no annotations provided, the description must disclose behavioral traits on its own. It does state that output includes 'requests with their response codes, line/word/char counts' and mentions 'auth handling' as a capability. However, it does not disclose potential side effects like network load, rate behavior, or prerequisites (e.g., network access, target reachability). It lacks depth about how the tool behaves during fuzzing, making it only partially transparent.

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?

The description is concise—three sentences—and front-loaded with a clear purpose ('Feature-rich web application brute-forcer'). It efficiently packs usage scenarios, a comparison to a sibling, and output format without wasted words. Every sentence contributes meaningful information.

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 network fuzzing tool with 100% schema coverage and no output schema, the description covers the main functional scope, usage cases, a key differentiator, and the output format. It lacks some practical context like typical command-line examples (though schema provides some) or guidance on handling authentication failures, but it is sufficiently complete for an agent to invoke the tool correctly in most scenarios.

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 each parameter already has a clear description (e.g., target includes an example with FUZZ keyword, opts includes an example command). The tool description itself adds no additional meaning about parameters; it only reinforces the tool's general purpose. Thus it stays at the baseline of 3 without adding extra value.

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?

The description clearly states the tool is a 'web application brute-forcer' that 'fuzzes URLs, POST data, headers, cookies, and authentication'. It identifies specific use cases (parameter discovery, login brute-force, etc.) and explicitly differentiates from sibling ffuf by claiming 'more flexible than ffuf for complex fuzzing'. This gives an agent a precise understanding of what the tool does and how it differs from alternatives.

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?

The description lists concrete application scenarios ('parameter discovery, login brute-force, header injection testing, and custom fuzzing scenarios') and provides a direct comparison to ffuf ('More flexible than ffuf for complex fuzzing'). However, it does not mention any exclusions or when NOT to use wfuzz (e.g., for simple directory brute-forcing where gobuster/dirb might be better), so it falls short of a full when/when-not distinction.

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