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Verify an Email Address

email_verify
Read-onlyIdempotent

Check whether an email address is real and safe to send to. Says if it will arrive or bounce (deliverable, undeliverable, risky, unknown), flags throwaway, role-based (info@, sales@), catch-all and free-mail addresses, and suggests a fix for typos like gmail.con. Use it before sending outreach or to clean up a sign-up list. Price: $0.02 per successful call; failed calls are free.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
emailYesThe email address to check, e.g. "jane@acme.com".
api_keyNoYour Unstuck API key, if this connection has none. Leave empty to try free tools or to get a key and payment link.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
emailYesThe address that was checked.
flagsYesAddress traits.
reasonYesWhy, e.g. mailbox_exists, invalid_syntax, disposable_domain, catch_all.
statusYesWhether mail to it will arrive.
checked_byYeslocal_precheck = answered by free local checks.
balance_usdYesRemaining prepaid balance, USD.
charged_usdYesAmount charged for this call, USD.
did_you_meanNoSuggested correction for a likely typo.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / api_key
      Added value: +{
      +  "description": "Your Unstuck API key, if this connection has none. Leave empty to try free tools or to get a key and payment link.",
      +  "maxLength": 200,
      +  "type": "string"
      +}
  2. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, open-world), but the description adds genuinely new operational context: per-call pricing ($0.02 per successful call, failed calls free) and the specific risk categories it detects. It does not mention rate limits, latency, or auth failure behavior beyond what the api_key schema field already states.

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, each earning its place: purpose first, detection categories second, use cases and cost last. No filler or restatement of the title.

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?

An output schema exists, so return values need not be spelled out. For a simple two-parameter read-only lookup, the description supplies purpose, detection scope, intended use, and cost — everything an agent needs to select and 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 description coverage is 100%, with both 'email' and 'api_key' documented in-schema, so the baseline is 3. The description adds no syntax, normalization, or format guidance for the email parameter beyond the schema's own example.

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 ('Check whether an email address is real and safe to send to') and enumerates the verdicts it returns (deliverable, undeliverable, risky, unknown). That framing clearly separates it from the sibling email_find, which discovers addresses rather than validating them.

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?

Gives concrete when-to-use contexts: 'before sending outreach' and 'to clean up a sign-up list.' It stops short of naming a when-not or an explicit alternative (e.g. use email_find to discover addresses), so it is clear but not fully routing.

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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