agentsvc-mcp

domain_check

Check a domain's registration, DNS records, and email security (SPF, DMARC, DKIM) in one call, returning a 0–100 score, grade, and findings.

Instructions

Domain and Email Security Check — Check a domain in one call: registration via RDAP (registered or likely available, registrar, created and expiry dates, status, nameservers; DNS fallback for TLDs without RDAP), DNS (A, NS, MX, CAA, DNSSEC) and email security (SPF, DMARC policy, DKIM on common selectors) with a 0 to 100 score, grade and findings. Params: domain (required). Cost: $0.009 USDC per call. Latency p99: 5000ms.

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": {
      "domain": "<domain>"
    },
    "name": "domain_check"
  }
}

Input Schema

Name	Required	Description	Default
`domain`	Yes	Domain name, e.g. example.com

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Oct 21, 2026

TDQS

A3.8/5.0

Behavior4/5

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

With no annotations, the description carries the full burden and does add real operational context: explicit cost ($0.009 USDC per call), p99 latency (5000ms), and the DNS-fallback behavior for TLDs without RDAP. It does not touch auth, rate limits, or failure modes, but the cost/latency disclosure is substantive beyond the schema.

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?

Everything fits in a tight, front-loaded block: purpose and scope first, then the parameter, then cost and latency. No filler sentences and each clause carries a distinct fact.

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?

No output schema exists, so the description correctly describes the return surface (0–100 score, grade, findings) along with the input and the composite scope. For a one-parameter tool this is nearly complete, missing only explicit sibling routing.

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% with a single required 'domain' parameter, so the schema already documents the input. The description only restates 'domain (required)' and adds no format or syntax detail beyond the schema's 'e.g. example.com'.

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

Purpose4/5

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

States a specific verb and resource (check a domain) and enumerates the concrete sub-checks it aggregates: RDAP registration data, DNS records, and email security (SPF/DMARC/DKIM). This implicitly distinguishes it from single-purpose siblings like whois or dns_lookup by framing it as a one-call composite, though it never names those alternatives outright.

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

Usage Guidelines3/5

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

The phrase 'in one call' implies this is the preferred bundle over running individual lookups, but there is no explicit when-to-use/when-not guidance and no mention of alternatives (whois, dns_lookup, email_validate). Usage is inferable rather than stated.

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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