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Official Porkbun MCP Server

List Invoices

list_invoices
Read-onlyIdempotent

Retrieve your Porkbun account's invoices, newest first, with date, state, net total, and domains. Filter by year and paginate to view or print each invoice page.

Instructions

List the account's invoices (one per order), newest first, with each one's date, state (PAID, PARTIALLY_REFUNDED, REFUNDED or UNPAID), net total in cents and the domains on it. total_cents is what the customer was left paying: refunds are netted out. Each invoice has url, its page on porkbun.com, which is the easiest thing to hand a user who wants to see or print one. Use get_invoice for the lines and get_invoice_pdf for the file.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearNoOnly invoices from this year, e.g. 2026.
limitNoInvoices per page, max 100. Default 50.
startNoPaging offset. Default 0.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.39.4

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive, so the safety burden is light. The description adds real context: newest-first ordering, that total_cents is refund-netted, the set of state values, and the presence of a print-ready url. It stops short of describing pagination behavior across pages.

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?

Three sentences, front-loaded with the action and its scope, then return-field nuances, then sibling routing. No wasted wording.

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?

No output schema exists, so the description must describe results — and it does: ordering, per-invoice fields, refund semantics, and the url. Combined with the fully-documented input schema, an agent has everything needed to call it correctly.

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 year, limit, and start are fully documented in the schema. The description adds nothing about these parameters beyond what the schema already states, which is the baseline expectation when the schema does the heavy lifting.

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 ('List the account's invoices'), scopes it ('one per order'), and characterizes the return shape (date, state, net total, domains, url). It is clearly distinguishable from get_invoice and get_invoice_pdf, which it names.

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 routes the agent: 'Use get_invoice for the lines and get_invoice_pdf for the file,' and notes that the url is the easiest thing to hand a user who wants to see or print one. When-to-use-this vs alternatives is fully covered.

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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