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DansPK

Kali MCP

by DansPK

list_payloads

List msfvenom payloads filtered by platform, architecture, or keyword to select the correct payload for your target before generating it.

Instructions

List all available msfvenom payloads with descriptions. Use BEFORE generating a payload to find the correct payload name for your target platform and connection type. Filter by platform (windows, linux, android), architecture (x86, x64), or keyword (reverse_tcp, bind, meterpreter). Output: table of payload names with descriptions, organized by platform.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
archNoFilter by architecture: x86, x64, armle, mipsle, ppc, aarch64
keywordNoKeyword to search within payload names (e.g. 'reverse_tcp', 'meterpreter', 'bind', 'https')
platformNoFilter by platform: windows, linux, android, osx, solaris, bsd

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries the behavioral disclosure. It states the output format ('table of payload names with descriptions, organized by platform') and the filtering capability. It does not explicitly mention that it's read-only, but the verb 'list' strongly implies it, and the output description clarifies the result. It could add caveats about large result sets, but that's minor.

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 two sentences plus a one-sentence output note. It front-loads the core action, provides usage timing, lists filters, and describes the output—no filler. Very efficient.

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 simple listing tool with no output schema and no annotations, the description covers the essential context: what it does, when to use it, how to filter, and what the response looks like. It could mention pagination or size, but given the tool's simplicity, it's sufficiently complete.

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?

The input schema already describes each parameter with 100% coverage. The description adds examples of filter values and connects them to use cases ('target platform and connection type'), but it lists only subsets of allowed values and does not elaborate on format or constraints beyond the schema. Value is marginal.

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 states a specific verb 'List' with a clear resource 'all available msfvenom payloads with descriptions,' and positions it as a pre-generation step, distinguishing it from related tools like msfvenom, list_encoders, and list_encryption. The purpose is unambiguous.

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?

It explicitly tells the agent when to use the tool: 'Use BEFORE generating a payload to find the correct payload name for your target platform and connection type.' It also explains filtering options with examples, though it doesn't explicitly name alternative tools for when not to use it. The context is clear enough.

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