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索引已觀測

SSearch

Free web search for AI agents. No API key required. Hosted MCP in active development.

我該用這個嗎

品質與安全性

A
說明品質
94%
結構描述完整度
73%
命名品質
100%
汙染風險
100%
權限相符程度
100%
協定合規性
100%

根據工具定義與協定合規性的自動化分析。

上下文成本

~588Token（工具定義）
~684 B典型回應大小
極小的注意力影響（128k 上下文的 0.46%）

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": {
    "search": {
      "url": "https://api.ssearch.cc/mcp"
    }
  }
}

遠端端點

https://api.ssearch.cc/mcpstreamable-http

它能做什麼

工具清單

工具（7）

🟢 唯讀🟡 寫入🔴 刪除⚪ 未知
🟡search_web(query, max_results, fresh, wait_for_coverage)

Search SSearch. Set wait_for_coverage to search owned documents and, only if needed, external discovery on a miss.

輸入結構描述

{
  "type": "object",
  "properties": {
    "query": {
      "title": "Query",
      "type": "string"
    },
    "max_results": {
      "default": 10,
      "title": "Max Results",
      "type": "integer"
    },
    "fresh": {
      "default": false,
      "title": "Fresh",
      "type": "boolean"
    },
    "wait_for_coverage": {
      "default": false,
      "title": "Wait For Coverage",
      "type": "boolean"
    }
  },
  "required": [
    "query"
  ],
  "title": "search_webArguments"
}
🟢search_documents(query, max_results, promote)

Search SSearch-owned stored full-text documents. Successful misses can be promoted into the live index.

輸入結構描述

{
  "type": "object",
  "properties": {
    "query": {
      "title": "Query",
      "type": "string"
    },
    "max_results": {
      "default": 10,
      "title": "Max Results",
      "type": "integer"
    },
    "promote": {
      "default": true,
      "title": "Promote",
      "type": "boolean"
    }
  },
  "required": [
    "query"
  ],
  "title": "search_documentsArguments"
}
🟢get_context(document_id, query, max_chars, max_passages)

Retrieve only the stored passages in a search result that are relevant to the information you need.

輸入結構描述

{
  "type": "object",
  "properties": {
    "document_id": {
      "title": "Document Id",
      "type": "string"
    },
    "query": {
      "title": "Query",
      "type": "string"
    },
    "max_chars": {
      "default": 5000,
      "title": "Max Chars",
      "type": "integer"
    },
    "max_passages": {
      "default": 5,
      "title": "Max Passages",
      "type": "integer"
    }
  },
  "required": [
    "document_id",
    "query"
  ],
  "title": "get_contextArguments"
}
🟢get_document(document_id, max_chars)

Retrieve the broader stored text for a known SSearch document ID.

輸入結構描述

{
  "type": "object",
  "properties": {
    "document_id": {
      "title": "Document Id",
      "type": "string"
    },
    "max_chars": {
      "default": 30000,
      "title": "Max Chars",
      "type": "integer"
    }
  },
  "required": [
    "document_id"
  ],
  "title": "get_documentArguments"
}
🟢fetch_page(url, archive_fallback, max_chars)

Fetch and extract readable page text; optionally fall back to Common Crawl.

輸入結構描述

{
  "type": "object",
  "properties": {
    "url": {
      "title": "Url",
      "type": "string"
    },
    "archive_fallback": {
      "default": true,
      "title": "Archive Fallback",
      "type": "boolean"
    },
    "max_chars": {
      "default": 30000,
      "title": "Max Chars",
      "type": "integer"
    }
  },
  "required": [
    "url"
  ],
  "title": "fetch_pageArguments"
}
🟢search_plan(query)

Show the normalized local search plan for a query.

輸入結構描述

{
  "type": "object",
  "properties": {
    "query": {
      "title": "Query",
      "type": "string"
    }
  },
  "required": [
    "query"
  ],
  "title": "search_planArguments"
}
🟢search_sources

Describe the local SSearch corpus and search backends.

輸入結構描述

{
  "type": "object",
  "properties": {},
  "title": "search_sourcesArguments"
}

建議的提示詞

research_workflow
Search for [topic], then get detailed information about the top results using SSearch
預期的工具： search_webget_context
search_research
Search for information about [topic] using SSearch
預期的工具： search_web
fetch_info
Fetch [information type] using SSearch
預期的工具： get_context
find_specific
Find [specific item] using SSearch
預期的工具： search_web
retrieve_data
Get details about [item] from SSearch
預期的工具： get_context

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已驗證未記錄版本7 個工具
已驗證未記錄版本7 個工具