MCP server

PeopleSearch.im Official

im.peoplesearch/email-finder

Checked 26 Oct 2026, 08:29 UTC · Connected to it and listed its tools

People search, LinkedIn lookup and verified work emails for AI agents. First search needs no login.

Website

At a glance

Type

MCP server

Publisher

peoplesearch.im (verified by the MCP Registry)

Status

Working at last check

Tools

13

Token cost

About 6,469 tokens per request

Sets up in

Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, VS Code, Antigravity, ChatGPT, OpenAI API, Grok

Last checked

26 Oct 2026, 08:29 UTC

Connect it to your agent

Add to CursorAdd to VS CodeVS Code Insiders

Opens the app, which shows the server and asks you to confirm. For other apps, copy the setup below.

Claude Code

claude mcp add --transport http email-finder https://peoplesearch.im/api/mcp

Claude Desktop

Settings → Connectors → Add custom connector, and paste the URL.

Codex (config.toml)

[mcp_servers.email-finder]
url = "https://peoplesearch.im/api/mcp"

Gemini CLI

{"mcpServers":{"email-finder":{"httpUrl":"https://peoplesearch.im/api/mcp"}}}

Cursor

{"mcpServers":{"email-finder":{"url":"https://peoplesearch.im/api/mcp"}}}

VS Code

{"servers":{"email-finder":{"type":"http","url":"https://peoplesearch.im/api/mcp"}}}

Antigravity

agy mcp add email-finder https://peoplesearch.im/api/mcp

ChatGPT

Settings → Apps & Connectors → Advanced settings: turn on Developer mode, then Create a connector and paste the URL. Which plans can do this varies.

OpenAI API (Responses tools)

{"type":"mcp","server_label":"email-finder","server_url":"https://peoplesearch.im/api/mcp","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"email-finder","server_url":"https://peoplesearch.im/api/mcp"}

Tools

• check_credits ~82 tokens
  Return the current credit balance for the API key making the request. Free and read-only. Use it before a large find_people call to confirm there are enough credits.
• company_search ~250 tokens
  Search a global company database and get matching companies with industry, size, location and website. Three ways to ask: a company's website ('warmly.ai') returns that one company, the most exact way to identify one; a company's name ('Warmly') returns the companies of that name; a description in p
• fetch_email ~204 tokens
  Look up the verified professional (work) email for a person you have already unlocked with find_people (or reveal_profile). Pass their `id`. Spends 1 credit, refunded automatically if no email is found. The lookup is live: if it returns emailStatus 'searching', call fetch_email again with the same i
• find_company_emails ~180 tokens
  Given a company domain or name, return the contactable role-based email addresses discovered for that organization (such as contact@, sales@, support@), each with a confidence level. Use this for reaching a company inbox, not a specific named person (for a named person use find_people or find_linked
• find_linkedin_profile ~188 tokens
  Find the LinkedIn profile URL for a named person. Provide their first and last name; adding the company or domain sharply improves the match. Spends 2 credits, refunded if no confident match is found.
• find_people ~2115 tokens
  The list-building tool. Runs a people search exactly as people_search does (the same `filters` or `query`, including its automatic broadening, reported in `broadenedBy`) and unlocks up to `count` full profiles in ONE atomic charge: 1 credit per newly unlocked person, and anyone you already own is fr
• find_work_email ~284 tokens
  Find and verify the professional (work) email of a person you can name: give their first name, last name and the company they work at (its domain, such as acme.com, matches best; a company name also works). Returns the address with a confidence label (Verified or Likely) and their LinkedIn profile w
• lookup_company ~121 tokens
  Turn a LinkedIn company URL into firmographic data: industry, size, location and website. Spends 1 credit, refunded if the company cannot be retrieved.
• lookup_linkedin_profile ~122 tokens
  Turn a LinkedIn profile URL into clean structured data: name, current role and company, and location. Spends 2 credits, refunded if the profile cannot be retrieved.
• people_search ~2356 tokens
  Search a global professional database for people and get a sample of matches plus the true total match count. Ask with `filters` (recommended: state each part exactly, for example {"job_titles": ["M&A Associate", "Investment Banking Associate"], "locations": ["Frankfurt", "Munich"], "industries": ["
• reveal_profile ~283 tokens
  Unlock ONE person from a people_search result. Pass the `token` from that result. Spends 1 credit and returns the full profile: real name, current title and company, location and LinkedIn URL. Set `include_email` to true to also look up their verified professional (work) email in the same call, whic
• reverse_email_lookup ~150 tokens
  Turn a professional email address into the real person behind it and their LinkedIn profile. Best for work emails; free-mailbox addresses often have no public profile to match. Spends 13 credits (this is the single most expensive lookup), refunded automatically if no match is found.
• verify_email ~134 tokens
  Check whether an email address exists and is safe to send to, before it bounces. Returns a deliverability verdict (deliverable, undeliverable, or unknown) without sending anything. Spends 1 credit, refunded if no verdict can be reached.

Browse

• Email
• Social media
• Company data
• Databases

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