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dns_lookup

Resolve DNS records and measure resolution time to diagnose slow or broken DNS. Supports A, AAAA, CNAME, MX, TXT, NS.

Instructions

Resolve DNS records for a name and report how long resolution took.

Answers: "Does this name resolve, to what, and is DNS itself slow or broken?" A/AAAA lookups go through the system resolver (socket.getaddrinfo) so they reflect what applications on this machine actually see; CNAME/MX/TXT/NS use dnspython.

Args: name: The DNS name to resolve (e.g. "vpn.example.com"). record_type: One of A, AAAA, CNAME, MX, TXT, NS (default "A").

Returns: On success: {"ok": true, "name", "record_type", "records": [...], "record_count", "resolution_time_ms"}. MX records are {"priority", "exchange"} dicts; other types are strings. On failure (NXDOMAIN, no answer, timeout): {"ok": false, "error": "..."}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
record_typeNoA

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses that A/AAAA lookups use the system resolver while CNAME/MX/TXT/NS use dnspython, and it reports resolution time. It does not cover rate limits or side effects, but for a read-only DNS lookup this is adequate.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with a purpose statement, usage context, implementation detail, and separate Args/Returns sections. It is slightly verbose but every part serves a purpose. The key info is front-loaded.

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?

Given the complexity (2 parameters, output schema present), the description is complete. It covers both success and failure response formats, distinguishes MX record structure, and includes error types (NXDOMAIN, timeout). The agent has enough context to use the tool correctly.

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?

Schema description coverage is 0%, leaving the description to fully explain parameters. It does so thoroughly, describing the 'name' parameter with an example, and 'record_type' with supported values and default. This adds significant value beyond the bare 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 explicitly states the tool resolves DNS records and measures resolution time, with a clear framing question ('Does this name resolve, to what, and is DNS itself slow or broken?'). It distinguishes well from sibling tools like ping_host or http_health by focusing on DNS resolution and timing.

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

Usage Guidelines4/5

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

The description answers when to use the tool by defining its purpose and the specific questions it addresses. However, it does not explicitly state when not to use it or mention alternative sibling tools, leaving some inference to the agent.

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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