Dechonet MCP

Lookalike Domain Check

lookalike_domains

Read-onlyIdempotent

Generate lookalike and typosquat domain variants of a given domain, then check their DNS registration status to identify potential phishing or brand impersonation risks.

Instructions

Generate the typosquat/lookalike variants of a domain that phishers actually register — homoglyph swaps (l→1, o→0, rn→m), TLD swaps (.com→.co), character omissions, transpositions, repetitions, hyphenations — and check which of them are currently registered (live NS delegation via DoH). Use this to assess brand-impersonation and phishing exposure for a domain the user is responsible for. A registered variant is NOT proof of abuse (it may be an unrelated legitimate site) — follow up with whois_lookup on each hit for its owner and registration date. Read-only; requires no API key; rate-limited. Returns generated/checked counts and the registered variants with the technique that produced each.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`domain`	Yes	Domain to protect (e.g., 'example.com'), without scheme or path. Variants of its label and TLD are generated and checked.

Output Schema

TableJSON Schema

Name	Required	Description
`kpis`	No	Key metrics as label/value pairs
`grade`	No	Letter grade (A+ to F) when the tool grades the target
`score`	No	0-100 score when the tool scores the target
`issues`	No	Detected problems, severity-rated
`status`	Yes	Overall verdict, e.g. 'good' \| 'warning' \| 'bad' \| 'info' \| 'unknown'
`actions`	No	Recommended next actions, most important first
`summary`	No	One-paragraph interpretation of the result
`reportUrl`	Yes	Human-facing interactive report for this exact lookup on dechonet.com

Schema Changelog

Changes observed during successful MCP inspections.

Addedv1.1.0Sep 8, 2026

TDQS

A5/5.0

Behavior5/5

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

The description clearly states behavioral characteristics: it is read-only, returns counts and registered variants with the technique, and warns that a registered variant is not proof of abuse. This aligns with the annotations (readOnlyHint: true, destructiveHint: false) and provides additional clarification about limitations.

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?

While the description is relatively long, every sentence contributes essential information, including purpose, techniques, output, and constraints. It is well-structured in a single paragraph without redundancy, making it appropriately concise for the tool's complexity.

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?

The description covers all necessary context: what the tool does, its output (counts and registered variants with technique), operational details (read-only, no API key, rate-limited), and follow-up actions (whois_lookup for ownership and registration date). It also explicitly addresses a common misconception about registered variants, making it highly complete.

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

Parameters5/5

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

The single parameter 'domain' is thoroughly described in the schema: it specifies the format (without scheme or path) and explains that variants of its label and TLD are generated. Schema coverage is 100%, and the description adds meaningful context about how the parameter is used.

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 clear purpose: generate typosquat/lookalike variants and check which are registered. It explicitly names the resource (domain), the scope (variants of label and TLD), and the use case (assessing brand-impersonation and phishing exposure).

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?

It provides explicit usage guidance: 'Use this to assess brand-impersonation and phishing exposure for a domain the user is responsible for.' It also notes the tool is read-only, requires no API key, is rate-limited, and recommends follow-up with whois_lookup, giving clear context for when and how to use it.

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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