QueryQuarry

QueryQuarry

Consent-based, double-blind talent marketplace. Recruiters' AI assistants search an anonymous corpus of opted-in candidates in natural language, evaluate match cards, and request contact — identity is revealed only when the candidate chooses to respond. Hosted remote server (streamable HTTP + OAuth) at queryquarry.com/api/mcp.

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Visit Server

README

<p align="center"> <img src="https://queryquarry.com/QueryQuarry_Logo_192.png" width="96" alt="QueryQuarry logo — an amber gem" /> </p>

<h1 align="center">QueryQuarry MCP Server</h1>

<p align="center"> <b>The consent-based talent graph recruiters' AIs query directly.</b><br/> Search an anonymous corpus of opted-in candidates in natural language — identity is revealed only when the candidate chooses to respond. </p>

<p align="center"> <a href="https://queryquarry.com">queryquarry.com</a> · <a href="https://queryquarry.com/docs/mcp">MCP docs</a> · <a href="https://queryquarry.com/blog">Blog</a> · <a href="mailto:hello@queryquarry.com">hello@queryquarry.com</a> </p>


QueryQuarry is a remote (hosted) MCP server for recruiters and sourcers. Instead of scraping or spraying InMails, your AI assistant queries a structured talent graph where every profile is explicitly opted in, candidates stay anonymous until they accept contact, and outreach happens through a double-blind escrow handshake.

Connect

Claude (claude.ai / Claude Desktop): Settings → Connectors → Add custom connector → https://queryquarry.com/api/mcp

Any MCP client (via mcp-remote):

{
  "mcpServers": {
    "queryquarry": {
      "command": "npx",
      "args": ["-y", "mcp-remote", "https://queryquarry.com/api/mcp"]
    }
  }
}

On first use you'll be sent through OAuth to link your recruiter account.

Tools

Tool What it does
search_candidates Search the talent graph. Returns anonymous match cards — headline, skills, seniority, location, availability, salary range. Rich filters: skills, location, remote, seniority, employment type, salary, experience, work authorization, relocation.
get_candidate Evaluate one candidate in depth (full skills, experience, education) — still anonymous. Metered.
request_contact Reach out: you identify yourself, the candidate is notified and decides. If interested, they contact you quoting a one-time code. Metered.
get_contact Status of a contact request: sent, accepted, or declined.
get_new_candidates Profiles new or updated since a timestamp — your standing alert.
save_candidate / get_watchlist Watchlist management.
get_corpus_stats Aggregate corpus stats — counts, top skills, top locations.
check_subscription Your tier, limits, and usage.
get_docs The full reference, served to your AI.

Full documentation: queryquarry.com/docs/mcp

How the double-blind flow works

  1. search_candidates → anonymous match cards, ordered by recency.
  2. get_candidate → deeper evaluation, still no name or contact info.
  3. request_contact → the candidate is notified with your identity and message.
  4. The candidate decides. If interested, they reach out to you with a one-time code. The platform never exposes a candidate's identity or contact details — consent is structural, not policy.

Pricing

Free accounts include an allowance of candidate reveals and contact requests. Paid plans: queryquarry.com/#pricing.


<p align="center">© 2026 QueryQuarry · This repository hosts documentation for the hosted MCP server; the service implementation is not open source.</p>

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