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Emitd MCP Server

Validate an email address

validate_email
Idempotent

Check one address before adding it as a contact or sending to a newly collected address. result is deliverable, risky (disposable, random-looking, or no MX record), undeliverable (bad syntax, no such domain, no mail server, or a previous hard bounce — do not send), or unknown (DNS unreadable right now; retry later). did_you_mean carries a corrected address when the domain looks like a typo — offer it to the user rather than sending to the original. 1,000 checks per workspace per day.

Input Schema

NameRequiredDescriptionDefault
emailYesThe address to check. Sent as typed — validation reports bad syntax rather than rejecting it.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior5/5

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

Adds substantial context beyond the annotations: it enumerates all four result states with their causes, explains the did_you_mean field and how to act on it, and discloses a concrete rate limit (1,000 checks per workspace per day) that explains the readOnlyHint=false quota consumption. This is exactly the behavioral detail annotations cannot carry.

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?

Front-loaded with the action and the when-to-use context, then packs result states, remediation guidance, and the rate limit into dense sentences with no filler. Every clause carries operational meaning.

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?

There is no output schema, yet the description effectively documents the return contract by defining result values and the did_you_mean field, so an agent knows exactly how to interpret and act on a response.

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% and the single email parameter is already documented as being sent as typed, so the description adds no parameter-level semantics beyond what the schema provides. Baseline 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 and resource ('Check one address') and situates it precisely in the workflow ('before adding it as a contact or sending'), which distinguishes it from the send-oriented siblings send_email and send_batch without naming them explicitly.

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 clear context for when to call it and what to do with each outcome ('do not send' on undeliverable, 'retry later' on unknown, offer did_you_mean to the user). It does not state explicit exclusions such as skipping checks for already-verified contacts, so it falls short of the 5 bar.

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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