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.
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.
- Endpoint:
https://queryquarry.com/api/mcp(streamable HTTP) - Auth: OAuth 2.0 — sign up at queryquarry.com, then connect your client and authorize
- Server card:
/.well-known/mcp/server-card.json
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
search_candidates→ anonymous match cards, ordered by recency.get_candidate→ deeper evaluation, still no name or contact info.request_contact→ the candidate is notified with your identity and message.- 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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