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jefferyleo

ezverify-mcp

by jefferyleo

Verify a list of email addresses (bulk job)

verify_emails_bulk

Submit an async bulk email verification job for up to 1,000 addresses and get a request_id to poll for results. Duplicates are billed once, and only definitive valid, invalid, or risky results use credits.

Instructions

Submit an async bulk email verification job (up to 1,000 emails per request; duplicate addresses are verified and billed once). Returns a request_id — poll with get_bulk_job_status. Uses credits: 1 credit per address with a definitive result (valid, invalid or risky), charged when the job completes; unknown results are free.

Input Schema

NameRequiredDescriptionDefault
emailsYesList of email addresses to verify
webhook_urlNoOptional public http(s) URL that gets one POST when the job completes. It carries counts only (campaign_id, which equals the request_id, plus total, valid, invalid, risky and unknown counts), not per-address results; fetch those with get_bulk_job_status. Delivered once, not retried.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.8

TDQS

A4.1/5.0
Behavior4/5

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

Goes well past the annotations, disclosing async behavior, the request_id return, credit cost (1 credit per definitive result), free unknown results, and duplicate-billing semantics. With annotations already covering readOnly/openWorld/idempotent hints, this adds substantial context; only rate limits or failure behavior are missing.

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 the action and cap, then the follow-up step, then cost. Dense and near-waste-free, though the parenthetical about billing is slightly nested.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, yet the description explains that the return is a request_id and how to retrieve results, and it describes the webhook payload via the schema. Complete for correct invocation, with only edge-case/failure behavior unaddressed.

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%, so the schema already defines both parameters and the webhook payload shape. The description adds only the 1,000-address cap and duplicate-billing semantics, which are useful but modest against a schema that does the heavy lifting; the baseline of 3 is appropriate.

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 ('Submit an async bulk email verification job'), the resource, and the scope (up to 1,000 emails per request). The word 'bulk' plus 'list' cleanly separates it from the single-address sibling verify_email.

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?

Clearly implies when to use it (bulk lists) and explicitly routes the follow-up step: 'poll with get_bulk_job_status'. It stops short of an explicit exclusion such as 'use verify_email for a single address', so the boundary with the single-verify sibling is inferred rather than stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.