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Official Porkbun MCP Server

Send Email Verification Code

send_email_verification_code

Email a verification code to the email address on the user's Porkbun account, to clear VERIFICATION_REQUIRED (purchases and top-ups need a verified email and phone). It is the usual verification email: a link plus a code.

Instructions

Email a verification code to the email address on the user's Porkbun account, to clear VERIFICATION_REQUIRED (purchases and top-ups need a verified email and phone). It is the usual verification email: a link plus a code. Then ask the user for the code in that email (or read it, if you have access to that inbox) and call confirm_email_verification; the user clicking the link works too. The address on the account is used (or a new address waiting for verification); it cannot be chosen or changed here, and the code is never returned to you: it only proves the address because it arrives there. A second request within 10 minutes returns codeAlreadySent; the earlier code stays valid for 3 days. Guide: https://porkbun.com/llms/guides/verify-the-account

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.51.1

TDQS

A4.9/5.0
Behavior5/5

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

Goes well beyond the annotations by disclosing rate-limit behavior (a second request within 10 minutes returns `codeAlreadySent`), code lifetime (3 days), the fact that the code is never returned (only proves ownership by arriving), and that the destination address cannot be chosen or changed here.

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?

Dense but front-loaded: the action, the target state, the follow-up, the constraints, and the rate-limit edge case arrive in that order, with no repeated or filler text.

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?

With no output schema, the description carries the return contract itself, naming the `codeAlreadySent` error and the code's validity window. Combined with the follow-up tool pointer and guide link, an agent has everything needed to call it and handle the result.

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

Parameters4/5

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

The tool takes zero parameters and the schema is empty, so there is no per-parameter semantics to add. The description still clarifies the key semantic point that the target address is implicit and cannot be supplied, which is the right baseline for a 0-param tool.

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?

States a specific verb and resource ('Email a verification code to the email address on the user's Porkbun account') and ties it to the concrete state it clears (VERIFICATION_REQUIRED). It is immediately distinguishable from send_phone_verification_code and routes the agent to confirm_email_verification.

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?

Explicitly states when to use it (purchases and top-ups need a verified email), names the follow-up alternatives (call confirm_email_verification, or the user clicking the link), and offers an external guide. Nothing about selection is left to inference.

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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