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Check email address

check_email_address
Read-onlyIdempotent

Use when you must check an email address before sending, signing up a user or adding a lead: syntax (IDN-aware), MX records with A/AAAA fallback, null MX, and disposable, role (info@, sales@). Returns the exact paid x402 request for your input (GET /v1/email/verify, $0.01 per call), with the response schema and an example; call that URL with an x402 or MPP client to get the data. Bad input is refused before any charge. Checks one mailbox; for a list use check_email_batch; for a whole domain (DNS, SPF, DMARC) use domain_report. With a P0 access key (header Authorization: Bearer p0k_…, buy one at https://x402-bazaar-rank.x402-bazaar-rank-worker.workers.dev/keys/buy?usd=5) this tool makes the paid call itself and returns the data, deducting the listed price.

Input Schema

NameRequiredDescriptionDefault
emailYesemail address to check, e.g. name@example.org

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.6/5.0
Behavior5/5

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

Annotations cover the safety profile (readOnly/idempotent/non-destructive), and the description adds what annotations cannot: the x402 payment flow, the $0.01 price, that bad input is refused before any charge, and that a P0 key makes the tool perform the paid call itself. This is exactly the economic and side-effect context an agent needs before invoking.

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?

Front-loaded with usage and check scope, then payment details, then alternatives — good ordering. It is dense and a single long block (payment, auth, and routing all run together), so minor points lost for structure, but every sentence carries distinct information.

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, and the description compensates by stating the tool returns the exact x402 request (GET /v1/email/verify, $0.01) with response schema and example, plus how to authenticate with a P0 key. An agent has everything needed to call and follow through.

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% and the single `email` parameter is documented with an example in the schema, so the description needn't restate it and largely doesn't. Baseline 3 is correct when the schema does the heavy lifting for a one-parameter 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+resource and enumerates exactly what is checked: syntax (IDN-aware), MX with A/AAAA fallback, null MX, disposable and role addresses. It also explicitly distinguishes itself from check_email_batch (lists) and domain_report (whole-domain DNS/SPF/DMARC).

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?

Opens with explicit trigger conditions ("before sending, signing up a user or adding a lead") and names two alternatives with the conditions that select them. Nothing is left to inference about when to use this vs siblings.

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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