@darkmoon_ai/mcp-server

Start a Darkmoon pentest

run_pentest

Launch an authorized autonomous penetration test against one target, returning a run ID for background polling and findings review.

Instructions

Start an autonomous Darkmoon penetration test against one authorized target. The run executes in the background and can take a long time. Returns the run_id; poll it with get_run_status and read results with get_findings once a campaign exists (list_campaigns). Only use against systems the user owns or has explicit written authorization to test. Findings can include false positives and must be reviewed by a qualified human.

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": {
      "target": "<target>"
    },
    "name": "run_pentest"
  }
}

Input Schema

Name	Required	Description
`focus`	No	Optional focus areas, e.g. ['auth', 'injection']
`target`	Yes	Host, URL or scope to assess. Only targets you are authorized to test.
`program`	No	Optional program name or rules-of-engagement note
`severity`	No	Optional minimum severity to report

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Oct 4, 2026

TDQS

A4.7/5.0

Behavior5/5

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

Annotations declare the operation is non-read-only, open-world, non-idempotent and non-destructive, but the description adds material behavior beyond them: the run is asynchronous and long-running, it returns a run_id rather than findings, and results are noisy and require qualified human review. The authorization precondition and false-positive caveat are exactly the kind of disclosure an agent cannot infer from annotations.

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?

Four tightly packed sentences with zero redundancy; the core action and target scope come first, then the asynchronous lifecycle, then the safety caveat. Every sentence contributes a distinct fact.

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

Completeness5/5

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

For an async kickoff tool with no output schema, the description supplies everything needed to invoke and follow up correctly: what it returns (run_id), the polling/reading path, the runtime characteristics, and the authorization and verification requirements. Nothing material is missing.

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 four parameters (target, focus, program, severity). The description only reinforces the target constraint with 'one authorized target' and adds no format, syntax or defaulting detail beyond the schema, so the baseline of 3 applies.

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 and resource ('Start an autonomous Darkmoon penetration test') plus the scope constraint ('against one authorized target'). The lifecycle sentence implicitly separates it from siblings by assigning get_run_status to polling, get_findings to result reading, and list_campaigns to campaign discovery, so an agent can position this as the entry point without opening another schema.

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

Usage Guidelines5/5

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

Explicitly names the alternatives and the conditions that select them ('poll it with get_run_status', 'read results with get_findings once a campaign exists (list_campaigns)'). It also states an explicit when-not-to-use condition: only systems the user owns or has written authorization to test.

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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