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OrtaMarco

domain-security-mcp-server

by OrtaMarco

DMARC Record Check

dmarc_check
Read-onlyIdempotent

Fetch and parse a domain's DMARC record to report policy, subdomain policy, reporting addresses, and alignment, with warnings for monitor-only or partial deployments.

Instructions

Fetch and parse a domain's DMARC record (_dmarc.). Reports the policy (p=), subdomain policy (sp=), reporting addresses (rua/ruf), pct and alignment (aspf/adkim), and warns on monitor-only or partial deployments.

Args:

  • domain (string): the domain to check.

  • response_format ('markdown' | 'json'): output format (default 'markdown').

Returns: { found, record, policy, tags{}, findings[] }.

Example: "What is paypal.com's DMARC policy?" -> dmarc_check(domain="paypal.com").

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
domainYesDomain to check, e.g. 'example.com'.
response_formatNoOutput format: 'markdown' for a human-readable summary (default) or 'json' for the full structured payload.markdown

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
domainYes
foundYes
recordNo
tagsYes
policyNo
findingsYes
Behavior4/5

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

Annotations already provide readOnlyHint=true, destructiveHint=false, and idempotentHint=true. The description adds behavioral details such as reporting policy components and warnings on monitor-only deployments, going beyond 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?

The description is concise and well-structured: first sentence states purpose, followed by arguments, return type, and an example. Every sentence adds value with no wasted words.

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?

Given the tool's simplicity and the presence of an output schema, the description adequately covers what the tool does and returns. However, it could mention error handling or DNS behavior for completeness.

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 coverage is 100%, so the schema fully documents both parameters. The description repeats the parameters and adds a default for response_format, but adds minimal new semantic value beyond the schema.

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 it fetches and parses a DMARC record, with specific verb and resource. It distinguishes itself from sibling tools like dkim_check and spf_check by focusing on DMARC policies.

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 description implies usage context through an example but does not explicitly state when to use this tool versus alternatives or when not to use it. No exclusions or alternative references are provided.

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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