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Glama
julcap

nginx-certbot-mcp

check_dns

Read-only

Resolve a domain against public DNS resolvers to verify it points where expected before issuing SSL certificates or creating a site.

Instructions

Resolve a domain (CNAME first, then A/AAAA) against public resolvers (1.1.1.1, 8.8.8.8) rather than this box's own DNS, so the result matches what Let's Encrypt and the public internet see. Use before issue_cert / create_site to confirm a domain actually points where you expect. For confirming something is listening behind nginx, use check_upstream_health instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
domainYesDomain to resolve, e.g. mysite.julcap.net

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
valuesNoResolved values (IPs, or the CNAME target); only present when resolves is true
resolvesYes
record_typeNoOnly present when resolves is true

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.1.1

TDQS

A4.5/5.0
Behavior4/5

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

Annotations provide readOnlyHint and openWorldHint, but the description adds behavioral nuance beyond that: it explains the resolution is against public resolvers to match Let's Encrypt's view, and mentions the query order. This is valuable context that isn't conveyed by annotations alone. No contradictions found.

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 (two sentences) and front-loaded with the core function and rationale. It avoids redundancy and each clause adds value—explaining the method, the use case, and the sibling alternative without fluff.

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 a simple read-only tool with one parameter, an output schema (which we don't see but is indicated), and annotations covering safety, the description is complete. It covers why the public resolver is used, when to call it, and how it differs from a nearby sibling, leaving no gap an agent would need filled.

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?

There is only one parameter, 'domain', and the input schema already provides a clear description with an example. The tool description doesn't add extra parameter-level details beyond what the schema covers, so it earns the baseline score for high schema coverage.

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 the tool's function: resolving a domain against public resolvers (1.1.1.1, 8.8.8.8) with a specific query order (CNAME first, then A/AAAA). It explicitly names the sibling tool check_upstream_health as the alternative for a different task, making its purpose unambiguous.

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?

The description explicitly states when to use the tool ('Use before issue_cert / create_site to confirm a domain actually points where you expect') and when not to ('For confirming something is listening behind nginx, use check_upstream_health instead'). This leaves no ambiguity about the tool's intended context.

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