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prospeo-v2

Prospeo MCP Server

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by prospeo-v2

enrich_person

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Find verified professional email and mobile for any person using LinkedIn URL, email, or name with company. Returns full profile with job history.

Instructions

Enrich a person — return their full profile with verified email and/or mobile, job history, and current company. Provide at least one identifier: linkedin_url, email, person_id (from a prior search result), or full_name/first_name+last_name plus company_name/company_website. Credits: 1 for email, 10 for email + mobile (set enrich_mobile=true; email is included free when mobile is requested). Credits are only deducted when the requested contact data is actually returned. No charge if no person is matched, and no charge if only_verified_email/only_verified_mobile is set but no verified contact exists. Check free_enrichment in the response to confirm.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
linkedin_urlNoLinkedIn profile URL, e.g. https://www.linkedin.com/in/johndoe
emailNoPerson's email address
person_idNoProspeo person_id from a prior Search Person result
first_nameNoPerson's first name
last_nameNoPerson's last name
full_nameNoPerson's full name (alternative to first_name + last_name)
company_nameNoCurrent employer name
company_websiteNoCompany website domain, e.g. acme.com
company_linkedin_urlNoCompany LinkedIn URL
only_verified_emailNoOnly return the result if a verified email is found
enrich_mobileNoAlso look up the person's mobile phone number (costs 10 credits; email is included at no extra cost when mobile is requested)
only_verified_mobileNoOnly return the result if a verified mobile is found (automatically enables enrich_mobile)
Behavior5/5

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

Describes credit system, when charges apply, and response field free_enrichment. Adds context beyond annotations (readOnlyHint, etc.). No contradiction with annotations; readOnlyHint aligns with read operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Succinctly packs purpose, identifier requirements, and billing details. Slightly long but every sentence adds value. Front-loaded with purpose.

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?

Adequately describes return value (full profile with email/mobile, job history, company) and includes free_enrichment field. No output schema, so description compensates reasonably.

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?

Adds meaning beyond schema by explaining the credit cost relationship between enrich_mobile and email, and the free_enrichment check. Schema already covers parameter descriptions, but description adds usage context.

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?

Clearly states the tool enriches a person by returning full profile with verified contact info. Distinguishes from siblings like search_person (which searches) and enrich_company (which enriches companies).

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?

Explicitly specifies required identifiers (linkedin_url, email, person_id, or name+company) and conditions for credit charges. Lacks explicit when-not-to-use or comparison to alternatives, but context is clear.

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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