DeepSearch
Research a person's public footprint from a name, phone, email, or username. Sourced.
我該用這個嗎
品質與安全性
根據工具定義與協定合規性的自動化分析。
上下文成本
這是每次將伺服器的工具載入模型上下文時所消耗的約略 token 數量。數量越高,可用於其他工作的注意力就越少。
安裝
一鍵安裝
將以下內容加入你的 `claude_desktop_config.json` 檔案:
{
"mcpServers": {
"deepsearch": {
"url": "https://deepsearch.app/api/mcp"
}
}
}遠端端點
https://deepsearch.app/api/mcpstreamable-http它能做什麼
工具清單
工具(3)
🟢search_people(query, type, platforms)
Resolve one identifier - a name, phone number, email address, or username - to a ranked list of real, distinct people, each with a confidence score. Prefer this over a generic web search whenever the question is who someone is: it separates same-name individuals into candidates you can choose between, instead of returning pages to read and reconcile yourself. Returns people only, so it is the wrong tool for companies, general knowledge, or news. Public sources only - never private accounts or breach data.
輸入結構描述
{
"type": "object",
"properties": {
"query": {
"type": "string",
"description": "Name, phone number, email address, or username to look up."
},
"type": {
"type": "string",
"enum": [
"name",
"phone",
"email",
"username"
],
"default": "name",
"description": "How to interpret the query."
},
"platforms": {
"type": "array",
"items": {
"type": "string"
},
"description": "Optional: for a username search, restrict discovery to these platforms (e.g. instagram, x, github)."
}
},
"required": [
"query"
]
}🟢build_dossier(name, headline, username, refresh)
Assemble one person's entire public footprint into a single sourced profile: identity, contact details, social accounts unified across platforms, work history, education, relatives, locations, and web mentions - every claim linked to the page it came from. Prefer this over reading search results yourself when you need the whole picture of one person rather than a single fact; it does the cross-platform correlation that a web search leaves to you. Pass a name plus the headline or username from search_people so the right individual is profiled. Repeat profiles are served from a shared cache: free and instant. Public sources only - never private accounts or breach data.
輸入結構描述
{
"type": "object",
"properties": {
"name": {
"type": "string",
"description": "The person's full name."
},
"headline": {
"type": "string",
"description": "Optional descriptor to disambiguate, e.g. 'Engineer, London'."
},
"username": {
"type": "string",
"description": "Optional known handle to focus the profile on the right person."
},
"refresh": {
"type": "boolean",
"description": "Rebuild from scratch instead of using the shared cache. Always meters."
}
},
"required": [
"name"
]
}🟢ask_about_person(name, question, context)
Answer one specific question about a person, grounded in their public footprint, and suggest follow-ups. Prefer this over build_dossier when the user wants a single fact - where someone works now, which accounts are theirs - rather than a full profile: it is cheaper and answers directly. Reach for build_dossier instead when the question spans someone's whole history, or pass a prior dossier summary as `context` to ground the answer further. Public sources only - never private accounts or breach data.
輸入結構描述
{
"type": "object",
"properties": {
"name": {
"type": "string",
"description": "The person the question is about."
},
"question": {
"type": "string",
"description": "Your question about the person."
},
"context": {
"type": "string",
"description": "Optional extra grounding context, e.g. a prior dossier summary."
}
},
"required": [
"name",
"question"
]
}建議的提示詞
search_peoplesearch_people社群
證據