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EnrowAPI

Enrow MCP Server

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by EnrowAPI

find_email

Find a professional email address from a full name and a company domain or name. Submit the search to receive an ID, then poll to retrieve the verified result.

Instructions

Find a professional email address from a name and a company domain or name. At least one of company_domain or company_name is required. Asynchronous: returns a search id, then poll get_email_result.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fullnameYesFull name of the person (e.g. "Tim Cook")
company_nameNoCompany name (e.g. "Apple Inc.")
country_codeNoISO 3166 Alpha-2 country code (default "US", used with company_name)
company_domainNoCompany domain (e.g. "apple.com")
retrieve_genderNoReturn gender information (male/female)
retrieve_company_infoNoEnrich the result with company info

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.1.0

TDQS

A4.4/5.0
Behavior4/5

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

The key behavioral trait—asynchronous execution returning a search id rather than the final email—is disclosed beyond what the annotations provide. With readOnlyHint=false, this two-step job behavior is consistent and useful, though failure modes or timeout expectations are not mentioned.

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 short sentences carry the purpose, the input constraint, and the async protocol with no redundant wording. The most important information 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?

For a start-search tool with no output schema, the description explains what is returned (search id) and the next tool to call (get_email_result), and parameter semantics are fully handled by the schema. It does not address bulk or verification sibling tools, but they are separate workflows and are not required to invoke this tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema already documents all parameters, so the baseline is 3. The description adds a valuable cross-field rule that the schema's required array does not capture: at least one of company_domain or company_name must be supplied, and they serve as alternative company keys.

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 opens with a specific action and object: 'Find a professional email address from a name and a company domain or name.' It also distinguishes this tool from the get_email_result sibling by stating it is asynchronous and returns a search id to poll.

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?

It gives a clear usage precondition ('At least one of company_domain or company_name is required') and an explicit follow-up action ('then poll get_email_result'). It does not name exclusions such as using find_emails_bulk for multiple lookups or verify_email for validation, so it stops short of full alternative 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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