queryquarry
Double-blind talent marketplace: AIs search anonymous opted-in candidates; reveal on consent.
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质量与安全性
基于对工具定义和协议合规性的自动分析。
上下文开销
这是每次将服务器的工具加载到模型上下文窗口时所消耗的大致 token 数。数值越高,可用于其他任务的注意力就越少。
安装
一键安装
将以下内容添加到你的 `claude_desktop_config.json` 文件中:
{
"mcpServers": {
"queryquarry": {
"url": "https://queryquarry.com/api/mcp"
}
}
}远程端点
https://queryquarry.com/api/mcpstreamable-http它能做什么
工具清单
工具(11)
🟢search_candidates(skills, location, radius_miles, remote_ok, experience_years_min, ...)
Search the talent graph. Returns ANONYMOUS match cards — headline, skills (with skills_matched showing which of YOUR terms hit), seniority, location, availability, salary range, and a short snippet — but NO name, full resume, or contact. Call get_candidate (a metered reveal) for the deeper anonymous profile. Filter by skills, location, seniority, salary, experience, availability, and more; sort by recency (default) or skill_match. Always paginated (max 25 per page).
输入模式
{
"type": "object",
"properties": {
"skills": {
"type": "array",
"items": {
"type": "string"
},
"description": "Skills to match (any of). Case-insensitive partial match — use plain terms like \"React\", \"Node\", \"Postgres\"; they also match versioned/variant skills (\"React 19\", \"Node.js\", \"PostgreSQL\")."
},
"location": {
"type": "string",
"description": "City with state (\"Schaumburg, IL\") or a 5-digit zip (\"60133\" — most precise). Geocoded locally; combine with radius_miles for distance search. Unresolvable text falls back to substring match."
},
"radius_miles": {
"type": "number",
"description": "With location: include candidates within this many miles (e.g. 5, 10, 25, 50; max 100). Omit for exact-place matching."
},
"remote_ok": {
"type": "boolean",
"description": "Only candidates open to remote/hybrid."
},
"experience_years_min": {
"type": "number"
},
"experience_years_max": {
"type": "number"
},
"availability": {
"type": "string",
"enum": [
"actively-looking",
"open-to-contact",
"employed-but-open"
]
},
"employment_types": {
"type": "array",
"items": {
"type": "string"
},
"description": "Engagement types to match (any of): full-time, part-time, contract, freelance, internship. Synonyms/variants are normalized."
},
"work_location_types": {
"type": "array",
"items": {
"type": "string"
},
"description": "Work-location preferences to match (any of): remote, hybrid, onsite."
},
"seniority_levels": {
"type": "array",
"items": {
"type": "string"
},
"description": "Seniority levels to match (any of): entry, junior, mid, senior, staff, principal, manager, director, executive."
},
"work_authorization": {
"type": "string",
"description": "Filter by work authorization: \"authorized\" (no sponsorship needed) or \"sponsorship-required\"."
},
"open_to_relocation": {
"type": "boolean",
"description": "Only candidates willing to relocate for the right role."
},
"salary_min": {
"type": "number"
},
"salary_max": {
"type": "number"
},
"updated_since": {
"type": "string",
"description": "ISO timestamp — only resumes updated since."
},
"page": {
"type": "number",
"description": "1-based page."
},
"limit": {
"type": "number",
"description": "Results per page (max 25)."
},
"sort": {
"type": "string",
"enum": [
"recency",
"skill_match"
],
"description": "Result order. When `skills` are supplied the default is skill_match: candidates matching MORE of your skills terms first (ties by most recently updated) — pure arithmetic over your own criteria, no fit scoring. Pass \"recency\" to order purely by recent updates; searches without `skills` are always recency-ordered."
}
}
}🟢get_candidate(candidate_id, resume_id)
Evaluate one candidate in depth — full skills, summary, seniority, experience (titles + what they did) and education. Stays ANONYMOUS: no name, no contact, and employer names, dates, and graduation years are withheld to protect identity. Counts toward your hourly/daily reveal limit. To actually reach someone, call request_contact.
输入模式
{
"type": "object",
"properties": {
"candidate_id": {
"type": "string"
},
"resume_id": {
"type": "string"
}
},
"required": [
"candidate_id",
"resume_id"
]
}🟢request_contact(candidate_id, resume_id, message)
Reach out to one candidate. You identify yourself (your name + company, from your account); the candidate is notified and decides. If they accept, you receive an EMAIL with their contact, their message, and a unique verification code — their identity stays private until they choose to share it. METERED (counts toward your contact limit) and requires a prior get_candidate for this resume. One active offer per candidate; respect declines. get_contact also shows the status any time.
输入模式
{
"type": "object",
"properties": {
"candidate_id": {
"type": "string"
},
"resume_id": {
"type": "string"
},
"message": {
"type": "string",
"description": "Your pitch to the candidate: the role and why them. Your account email is AUTOMATICALLY attached and shown to them when they express interest, so you don't need to include it. You may optionally add other ways to connect (an application form link, your LinkedIn, etc.). Shown in-app, not your raw query."
}
},
"required": [
"candidate_id",
"resume_id",
"message"
]
}🟢get_contact(contact_id, code)
Check the status of a contact request you sent: sent (awaiting), accepted (the candidate shared their contact — see shared_contact, and expect their intro email quoting the code), or declined. Identify it by contact_id or code. Also shows any hire outcome either side reported.
输入模式
{
"type": "object",
"properties": {
"contact_id": {
"type": "string"
},
"code": {
"type": "string"
}
}
}⚪report_contact_outcome(contact_id, code, outcome)
One-tap outcome report on an accepted contact: did it lead to a hire? Optional but appreciated — it's how the marketplace measures that consented outreach beats cold outreach. Values: hired | not_hired | in_progress.
输入模式
{
"type": "object",
"properties": {
"contact_id": {
"type": "string"
},
"code": {
"type": "string"
},
"outcome": {
"type": "string",
"enum": [
"hired",
"not_hired",
"in_progress"
]
}
},
"required": [
"outcome"
]
}🟢get_new_candidates(since)
Get resumes new or updated since a timestamp (your standing alert). Same filters as search_candidates. Call daily with yesterday's timestamp; no duplicates.
输入模式
{
"type": "object",
"properties": {
"since": {
"type": "string",
"description": "ISO timestamp."
}
},
"required": [
"since"
]
}🟡save_candidate(candidate_id, resume_id, notes)
Save a candidate resume to your watchlist with optional notes.
输入模式
{
"type": "object",
"properties": {
"candidate_id": {
"type": "string"
},
"resume_id": {
"type": "string"
},
"notes": {
"type": "string"
}
},
"required": [
"candidate_id",
"resume_id"
]
}🟢get_watchlist(status, page)
Get your saved candidates (watchlist).
输入模式
{
"type": "object",
"properties": {
"status": {
"type": "string"
},
"page": {
"type": "number"
}
}
}🟢get_corpus_stats
Get aggregate stats about the talent corpus (counts, top skills/locations).
输入模式
{
"type": "object",
"properties": {}
}🟢check_subscription
Check your subscription tier, status, rate limit, and usage this hour.
输入模式
{
"type": "object",
"properties": {}
}🟢get_docs
Get the full QueryQuarry reference (how it works, all tools and filters, search tips, rate limits, privacy). Call this when you need detail beyond these tool descriptions, when guiding a new user, or before composing a complex search.
输入模式
{
"type": "object",
"properties": {}
}社区
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