About queryquarry
QueryQuarry is a hosted MCP server for recruiters and sourcers to search an opted-in talent graph through AI. Candidates remain anonymous and can respond to contact requests through a double-blind process.
Key features
- 01Search talent by skills, location, and criteria
- 02Review candidate profiles anonymously
- 03Request contact with candidate consent
- 04Check contact request status
- 05Manage watchlists and new candidates
Use cases
- 01Find candidates matching a role
- 02Assess experience without revealing identity
- 03Request consent before contacting a candidate
- 04Track newly added or updated candidates
MCP support
The hosted MCP server provides talent search, profile review, contact requests, and watchlist tools over Streamable HTTP with OAuth 2.0. Candidate identity and contact details are not shown to recruiters; candidates choose whether to respond through the contact flow.
Configuration
Remote servers need no local install. Pick your client, then copy the config or install in one click.
https://queryquarry.com/api/mcpclaude mcp add --transport http queryquarry-queryquarry https://queryquarry.com/api/mcp{"mcpServers":{"queryquarry-queryquarry":{"type":"http","url":"https://queryquarry.com/api/mcp"}}}Open in Cursor{"servers":{"queryquarry-queryquarry":{"type":"http","url":"https://queryquarry.com/api/mcp"}}}Open in VS Code{"mcpServers":{"queryquarry-queryquarry":{"type":"http","url":"https://queryquarry.com/api/mcp"}}}{"mcpServers":{"queryquarry-queryquarry":{"serverUrl":"https://queryquarry.com/api/mcp"}}}Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.
Tools
Details
From the project README
QueryQuarry MCP Server
The consent-based talent graph recruiters' AIs query directly.
Search an anonymous corpus of opted-in candidates in natural language — identity is revealed only when the candidate chooses to respond.
queryquarry.com · MCP docs · Blog · [email protected]
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.
© 2026 QueryQuarry · This repository hosts documentation for the hosted MCP server; the service implementation is not open source.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.