Skip to main content
Glama

Millionverifier

Millionverifier Verify

millionverifier_verify
Read-onlyIdempotent

Verify a single email address with MillionVerifier. Returns result (ok/catch_all/disposable/invalid/unknown), a quality label, and free/role flags. Example: millionverifier_verify({ email: "jane@stripe.com", _apiKey: "your-millionverifier-key" })

Input Schema

NameRequiredDescriptionDefault
emailYesEmail address to verify, e.g. "jane@stripe.com"
_apiKeyYesYour MillionVerifier API key (find it at app.millionverifier.com/api).
timeoutNoSMTP timeout in seconds, 2-60 (default 20).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, open-world and non-destructive behavior, and the description adds real value by listing the return categories (ok/catch_all/disposable/invalid/unknown) plus quality and free/role flags. It stops short of mentioning cost/credit consumption or error semantics for 'unknown', which would complete the picture.

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 tight sentences: purpose, return values, example. Zero filler and the core action is front-loaded.

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?

With no output schema, the description usefully enumerates return categories, and the schema fully documents inputs. Only the cost/credit implications and behavior on provider failure are unaddressed, which are minor for a single-address read-only check.

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 email, _apiKey and timeout are all already documented by the schema. The description only adds a redundant example call and repeats the email parameter, so the baseline 3 applies.

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 ('Verify a single email address') and names the provider. It also enumerates the result categories returned, so an agent knows exactly what operation this performs without opening the schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage through a concrete example call, but never states when to use this versus not, nor any prerequisites such as needing a valid API key or that each verification may consume credits. No sibling tool overlaps, so implied usage is adequate but thin.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.