Sofya

Web search, fetch, extract, and research for AI agents. Markdown output + AI-synthesized answers.

我该使用它吗

质量与安全性

A
描述质量
100%
模式完整度
77%
命名质量
90%
投毒风险
100%
权限匹配度
100%
协议合规性
100%

基于对工具定义和协议合规性的自动分析。

上下文开销

~1,379token 数(工具定义)
~1.0 KB典型响应大小
对注意力有中等影响(占 128k 上下文窗口的 1.08%)

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": {
    "sofya": {
      "url": "https://sofya.co/mcp"
    }
  }
}

远程端点

https://sofya.co/mcpstreamable-http

它能做什么

工具清单

工具(4)

🟢 只读🟡 写入🔴 删除⚪ 未知
🟡search(query, search_depth, max_results, include_answer, include_domains, ...)

Search the web for current information on any topic. Returns extracted page content, not just snippets. Best for factual lookups, specific questions, or when you need a list of sources. For open-ended questions that need synthesis across many sources, use the research tool instead. For news queries (current events, breaking news, politics, world events), set topic="news" to search news sources specifically. This returns recent articles with publication dates. Set include_answer=true to get an AI-synthesized answer alongside results (adds 10 credits). This is the sweet spot for most agent tasks, e.g. basic + include_answer = 12 credits, much cheaper than a full 50-credit research call. Returns: query, answer (if requested), results (array of {title, url, content, description, fetched, published_date}), search_depth, topic, elapsed_ms, credits_used, credits_remaining, altered_query, relaxed_query (set when the query matched nothing and was retried once with its site: operator, else its quotes, removed - the results answer that looser query). Args: query: The search query search_depth: "basic" (default) for extracted page content (2 credits), "snippets" for SERP snippets only without page fetching (1 credit) max_results: Number of results (default 10, max 20) include_answer: Generate an AI answer that synthesizes the search results (adds 10 credits) include_domains: Only include results from these domains (max 10) exclude_domains: Exclude results from these domains (max 10) topic: "general" for web search, "news" for news articles. use "news" for current events, breaking news, politics, or any time-sensitive query freshness: Filter by recency - "day", "week", "month", "year", or "YYYY-MM-DD:YYYY-MM-DD"

输入模式

{
  "type": "object",
  "properties": {
    "query": {
      "type": "string",
      "title": "Query"
    },
    "search_depth": {
      "type": "string",
      "default": "basic",
      "title": "Search Depth"
    },
    "max_results": {
      "type": "integer",
      "default": 10,
      "title": "Max Results"
    },
    "include_answer": {
      "type": "boolean",
      "default": false,
      "title": "Include Answer"
    },
    "include_domains": {
      "anyOf": [
        {
          "type": "array",
          "items": {
            "type": "string"
          }
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "title": "Include Domains"
    },
    "exclude_domains": {
      "anyOf": [
        {
          "type": "array",
          "items": {
            "type": "string"
          }
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "title": "Exclude Domains"
    },
    "topic": {
      "type": "string",
      "default": "general",
      "title": "Topic"
    },
    "freshness": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "title": "Freshness"
    }
  },
  "required": [
    "query"
  ]
}
🟡fetch(urls, include_raw_html)

Fetch one or more URLs and return their content as clean markdown. Use this to read articles, documentation, blog posts, or any page where you need the complete text, not just a snippet from search. Also supports PDF, DOCX, and other document formats. Costs 2 credits per URL. Max 10 URLs per request. Failed URLs are not charged. Set include_raw_html=true to also get the raw HTML source in each result. Useful for inspecting embedded URLs, data attributes, iframes, or script tags that are stripped during markdown conversion. Returns null for non-HTML content (PDF, DOCX, etc.). Same cost. Returns: results (array of {title, url, content, raw_html, published_time, success, error}), credits_used, credits_remaining. Args: urls: List of URLs to fetch (max 10) include_raw_html: Include raw HTML source in each result (default false)

输入模式

{
  "type": "object",
  "properties": {
    "urls": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "maxItems": 10,
      "title": "Urls"
    },
    "include_raw_html": {
      "type": "boolean",
      "title": "Include Raw Html",
      "default": false
    }
  },
  "required": [
    "urls"
  ]
}
🟢extract(url, prompt)

Fetch a webpage and extract specific information using AI. Use this when you need structured data from a page (e.g. pricing, specs, contact info) rather than the raw content. Costs 10 credits. If the page has no usable text (empty or JavaScript-rendered body), the model is NOT called: content comes back empty and usage.low_content is true, rather than a fabricated answer. Gate on usage.low_content (or usage.content_chars) to detect pages you cannot ground on. Returns: content (the extracted text), url, credits_used, credits_remaining, usage (input_tokens, output_tokens, content_chars, low_content). Args: url: The URL to extract from prompt: What information to extract (e.g. "list all pricing tiers with features" or "extract the author name and publication date")

输入模式

{
  "type": "object",
  "properties": {
    "url": {
      "type": "string",
      "title": "Url"
    },
    "prompt": {
      "type": "string",
      "title": "Prompt"
    }
  },
  "required": [
    "url",
    "prompt"
  ]
}
🟢research(query, topic, freshness, max_sources)

Perform comprehensive research on a topic. Decomposes your query into sub-queries, searches and reads multiple sources in parallel, then synthesizes a structured report with citations. Best for open-ended or comparative questions that need coverage from many angles. For simple factual lookups, use search instead (optionally with include_answer=true for cheap synthesis). Costs 50 credits. Returns: query, report (structured markdown with citations), sources (array of {title, url, fetched}), sub_queries (the decomposed queries), credits_used, credits_remaining, usage (token counts). Args: query: The research question or topic topic: "general" (default) or "news" (prioritize recent news articles) freshness: Filter by recency - "day", "week", "month", "year", or "YYYY-MM-DD:YYYY-MM-DD" max_sources: Maximum number of sources to use, 5-30 (default 20)

输入模式

{
  "type": "object",
  "properties": {
    "query": {
      "type": "string",
      "title": "Query"
    },
    "topic": {
      "type": "string",
      "default": "general",
      "title": "Topic"
    },
    "freshness": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "title": "Freshness"
    },
    "max_sources": {
      "type": "integer",
      "default": 20,
      "title": "Max Sources"
    }
  },
  "required": [
    "query"
  ]
}

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最近观测

已验证未记录版本4 个工具
已验证未记录版本4 个工具