LeadEnrich MCP Server

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find_email

Retrieves a professional email address using a person's name and company domain, querying Hunter email finder first and falling back to Apollo if needed.

Instructions

Find someone's email address given their name and company domain.

Uses Hunter email-finder first (purpose-built for this), then falls back to Apollo people-match if Hunter doesn't find it.

Input Schema

TableJSON Schema

Name	Required	Description
`first_name`	Yes	Contact's first name.
`last_name`	Yes	Contact's last name.
`domain`	Yes	Company domain (e.g. "stripe.com").
`api_key`	No	Your LeadEnrich API key for usage tracking.

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.2.0May 27, 2026

TDQS

A4.3/5.0

Behavior4/5

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

With no annotations, the description notably discloses the fallback behavior (Hunter then Apollo). This adds transparency beyond basic functionality, though it omits details like rate limits or error handling.

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 key purpose and fallback logic are front-loaded.

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?

The description is complete for a lookup tool: it explains the core function and fallback strategy. An output schema exists, so return values need not be detailed.

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 schema already documents each parameter. The description adds no new semantic detail beyond restating the purpose.

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 clearly states the tool's action: finding an email address given name and domain. It distinguishes from siblings like enrich_lead, which serve different purposes.

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?

The description indicates when to use: looking up an email by name and domain. It mentions the fallback strategy but does not explicitly state when not to use or alternatives among siblings.

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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