Personal Email to Company Resolver MCP Server
Resolve likely employers behind personal email addresses and return structured evidence and confidence data.
Resolve one
emailor up to 300emailsper run.Use public Gravatar profiles, GitHub signed-commit accounts, optional exact Google searches, and optional LinkedIn URL resolver.
Return per-address
person_name,employer_name,employer_domain,employer_source,employer_confidence,match_status, LinkedIn URL, andevidence_urls.Handle statuses such as
resolved,weak,name_only,corporate_email,not_found,invalid_email, andblocked.Return a corporate email domain directly for free.
Supports
country,max_charge_usd,github_token,search_web, anduse_linkedin_resolveroptions.Requires
APIFY_TOKEN; it is read-only and never contacts the mailbox or opens LinkedIn.
Finds GitHub accounts whose public commits are signed with the given email address, using an optional GitHub token, to infer identity and employer information.
Runs exact Google searches for addresses without an employer to gather public web evidence and improve employer resolution.
Reads public Gravatar profiles for a given email address to help identify the person's name and likely employer.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Personal Email to Company Resolver MCP Server Who does alice.jones@gmail.com work for? Show evidence."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Personal Email to Company Resolver MCP Server
Give it a free mail address (Gmail, Outlook, iCloud, Yahoo, and about 140 more consumer domains). Each run reads the public Gravatar profile for the address, the GitHub account whose public commits are signed with it, and, for a name with an employer, Mamba Labs Person LinkedIn URL Resolver. It returns one row per address with the person's name, likely employer, employer domain, and a confidence. It never contacts the mailbox and never opens LinkedIn.
What's Inside
Related MCP server: xposedornot
What it does
match_statusisresolved(employer at 0.75 or more, billed),weak,name_only,corporate_email,not_found,invalid_email, orblocked, and onlyresolvedis billed.employer_sourcesays where the employer came from:gravatar,github,web_result,linkedin_headline, oremail_domain.evidence_urlslists the public pages.The LinkedIn step raises the confidence when a LinkedIn result shows the employer as current and lowers it when it shows it as former.
All of the work runs on Apify. This package is a thin client that starts the actor run, waits for it, and hands back the dataset rows.
Quick start
You need Node.js 18 or newer and an Apify account with an API token.
Add this to your Claude Desktop config (claude_desktop_config.json), Cursor, or any MCP client:
{
"mcpServers": {
"mamba-personal-email-to-company-resolver": {
"command": "npx",
"args": [
"-y",
"@mambalabsdev/mcp-personal-email-to-company-resolver"
],
"env": {
"APIFY_TOKEN": "your-apify-token"
}
}
}
}Restart the client. The resolve_personal_email_employer tool appears.
Prerequisites
Node.js 18 or newer.
An Apify API token from console.apify.com/account/integrations, set as
APIFY_TOKEN. The server lists its tool without a token; a call needs one.
Example prompts
"These ten signups used Gmail addresses. Which companies do they work at?"
"Find the employer behind this Outlook address and show me the evidence."
Tool
resolve_personal_email_employer. One tool. Example arguments:
{ "emails": ["sample.signup@gmail.com"] }Inputs
Every buyer facing input of the actor, unchanged. Omitted inputs take the actor's own defaults.
Input | Type | Description |
| string | One address |
| array | Up to 300 addresses |
| string | Optional, your own free GitHub token |
| string | true adds one exact Google search per address left without an employer. Default false |
| string | true (default) runs Person LinkedIn URL Resolver from your account, billed at its own price |
| string | Google country code. Default us |
| string | Optional cost cap for the run |
Pricing
Pay per event on Apify, billed to your Apify account. Prices in USD.
Event | Free plan | Bronze | Silver | Gold |
| $0.025 | $0.02375 | $0.0225 | $0.02125 |
| $0.0005 | $0.0005 | $0.0005 | $0.0005 |
Every other row is free. With use_linkedin_resolver on, Person LinkedIn URL Resolver bills its own events on top: $0.035 per person sent to it, found or not, plus $0.0005 per run on the free plan.
Your keys
The actor holds no key. github_token is optional and is your own, used for the run only. Mamba Labs pays the platform costs of the run, proxy traffic included.
Full actor documentation
apify.com/mambalabs/personal-email-to-company-resolver
License
MIT. See LICENSE.
Available Tools
1 toolresolve_personal_email_employerResolve the employer behind a personal emailARead-only
Find the likely employer behind a free mail address (Gmail, Outlook, iCloud, Yahoo, and about 140 more), from the public Gravatar profile for the address, the GitHub account whose public commits are signed with it, and Mamba Labs Person LinkedIn URL Resolver. Returns one row per address with person_name, employer_name, employer_domain when a source names it, employer_source, employer_confidence from 0 to 1, match_status (resolved at 0.75 or more, weak, name_only, corporate_email, not_found, invalid_email, blocked), the LinkedIn URL when found, and evidence_urls. It never contacts the mailbox and never opens LinkedIn. A run that does not succeed is returned as an error with its run ID. Read-only; requires an APIFY_TOKEN; Apify charges per resolved address, and the optional LinkedIn step is billed by Person LinkedIn URL Resolver at its own price.
Inputs: email, emails, country, search_web, +3 more.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
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TDQS
Scored across 1 tool
There is only one tool, so there is no possibility of misselection between tools. Its purpose (resolve the employer behind a personal email address) is stated explicitly and unambiguously.
The single name resolve_personal_email_employer is descriptive snake_case with a clear verb_noun_qualifier structure. With only one tool there is no convention clash, and the name reads predictably.
A single-purpose resolver plausibly needs only one operation, and the tool accepts multiple addresses per call, so the count is not wrong. However, one tool is a thin surface for a billed, asynchronous Apify actor, leaving no companion operation for run inspection or cost checks.
The tool covers the full resolution lifecycle for its narrow domain: multiple input addresses, rich per-row output (name, employer, domain, source, confidence, match_status, LinkedIn URL, evidence), and documented failure statuses. The main gap is that failed runs only return a run ID with no tool to retrieve that run's results or status, which is a dead end for recovery.
Maintenance
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