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Email Verifier

email_verifier
Read-onlyIdempotent

Verify an email address with Hunter.io email verification. Checks deliverability, MX records, SMTP, and whether the address is disposable or webmail. Returns a status, result, and confidence score. Example: email_verifier({ email: "patrick@stripe.com" })

Input Schema

NameRequiredDescriptionDefault
emailYesEmail address to verify, e.g. "patrick@stripe.com"
_apiKeyNoOptional — your own Hunter.io API key for higher limits; omit to use the shared Pipeworx key.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
      +  {
      +    "email": "patrick@stripe.com"
      +  },
      +  {
      +    "email": "contact@github.com"
      +  }
      +]
  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 indicate readOnlyHint, idempotentHint, and not destructive. The description adds valuable behavioral context: the types of checks performed (MX, SMTP, disposable, webmail) and the output format (status, result, confidence score). No contradictions.

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?

Two sentences plus an example, no wasted words. Information is front-loaded and easy to parse. Every sentence earns its place.

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?

Although there is no output schema, the description adequately explains what the tool returns (status, result, confidence score) and lists the verification checks. Annotations cover safety and idempotency. No gaps for the tool's complexity.

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% with both parameters described. The description adds example values and clarifies that the email is the target, but does not explain the _apiKey parameter beyond what the schema provides. Baseline 3 is appropriate as the description adds marginal semantic value.

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?

The description clearly states the action ('Verify an email address') and the resource (Hunter.io). It enumerates specific checks (deliverability, MX records, SMTP, disposable/webmail) which distinguishes it from siblings like email_finder and domain_search.

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?

The description implies use when an email's deliverability needs confirmation, but does not explicitly state when not to use or name alternatives. The sibling list provides context but the description itself lacks exclusions.

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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