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EnrowAPI

Enrow MCP Server

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by EnrowAPI

find_phone

Get a mobile number using a LinkedIn URL or name and company details. Submit the query, receive a search ID, then poll for the result.

Instructions

Find a mobile phone number from a LinkedIn URL (recommended) or first name + last name + company. Asynchronous: returns a search id, then poll get_phone_result.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
last_nameNoLast name
first_nameNoFirst name
company_nameNoCompany name
linkedin_urlNoLinkedIn profile URL (recommended; takes precedence)
company_domainNoCompany domain

Schema Changelog

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

  1. First observedv1.1.0

TDQS

A4.2/5.0
Behavior4/5

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

The description discloses the asynchronous behavior—returns a search id, then requires polling get_phone_result—which is critical context not present in the annotations. It avoids contradicting readOnlyHint=false or destructiveHint=false, and adds useful behavioral depth beyond what annotations provide.

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 with no wasted words. The core purpose is front-loaded, and the async caveat is placed immediately after, giving the agent the essential information in minimal space.

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 tool with five optional parameters and no output schema, the description covers the main input variants and the follow-up polling step. It does not describe the result payload or polling timeout, but the explicit reference to get_phone_result compensates for that gap.

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%, so the baseline is 3. The description adds meaningful selection guidance by marking linkedin_url as recommended and indicating first_name, last_name, and company_name can be used as a combined lookup. However, it omits any mention of company_domain, leaving part of the schema unaddressed in the narrative.

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 identifies a specific action ('find') and resource ('mobile phone number'), and states the two input modes: LinkedIn URL or name + company. This clearly distinguishes it from email-oriented siblings like find_email and bulk variants.

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 explicitly recommends LinkedIn URL as the preferred input and provides the alternative name + company lookup. It also tells the agent to poll get_phone_result after receiving a search id, which is a concrete next step. It does not contrast with find_phones_bulk, but the guidance is sufficient for basic 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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