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Verify an email address (paid)

email_verify
Read-onlyIdempotent

Email verification and validation for signup, CRM, lead and outreach agents: RFC syntax, live DNS mail routing (MX, null MX, implicit MX), 9,000+ disposable/throwaway domains, role addresses (info@, sales@), free providers, typo suggestions (gmial.com to gmail.com) and the domain SPF/DMARC setup. One verdict: deliverable, risky or undeliverable. Domain lookups cached for speed. Costs 0.002 USDC via x402, or 1 credit of a Factline API key.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
emailYesEmail address, e.g. jan@example.nl

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.4/5.0
Behavior5/5

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

Annotations already declare readOnly, idempotent and openWorld, but the description goes well beyond them: it discloses the cost model and payment path (0.002 USDC via x402 or 1 Factline credit), the caching behavior for domain lookups, and the exact output taxonomy (deliverable / risky / undeliverable). This is exactly the class of pre-purchase behavior an agent needs before invoking a paid tool.

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 check inventory is front-loaded and every clause carries distinct information (syntax, DNS, disposable lists, role addresses, typo suggestions, SPF/DMARC). The first sentence is long and list-like, but nothing is padding and the pricing sentence is short and load-bearing.

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 takes on the return-value burden and does so by naming the single verdict and its three values. Combined with cost, caching and the full check list, an agent has everything needed to decide and call 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?

Only one parameter and schema coverage is 100%, including an example address, so the schema already carries the parameter burden. The description adds no input-side semantics such as normalization or batching behavior; the typo example (gmial.com to gmail.com) describes output, not input.

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 (email verification and validation) and enumerates exactly what is checked: RFC syntax, live DNS/MX routing, disposable domains, role addresses, free providers, typo suggestions, SPF/DMARC. This clearly separates it from siblings like phone_verify and eu_vat_check without opening any schema.

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?

Names concrete applicability contexts (signup, CRM, lead and outreach agents), which tells the agent when this tool fits. It does not name an alternative or state any exclusion (e.g. when not to verify, or that phone_verify covers the phone analogue), so it stops short of explicit routing guidance.

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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