summarize_webpage

Extract and condense webpage content to a specified length, providing concise summaries for quick understanding. Input a URL and set target compression ratio for tailored results.

Instructions

抓取网页内容并总结为指定比例的长度（默认20%）

Args:
    url: 要抓取和总结的网页URL
    target_ratio: 目标压缩比例，0.1-1.0之间

Returns:
    网页内容总结

Input Schema

TableJSON Schema

Name	Required	Description	Default
`target_ratio`	No
`url`	Yes

Implementation Reference

src/fullscope_mcp_server/server.py:368-399 (handler)

The primary handler function for the 'summarize_webpage' tool. It validates parameters, scrapes the webpage using the WebScraper instance, summarizes the title and content using the ContentSummarizer instance, and returns a formatted summary with title and URL.

@mcp.tool()
async def summarize_webpage(url: str, ctx: Context, target_ratio: float = 0.2) -> str:
    """
    抓取网页内容并总结为指定比例的长度（默认20%）
    
    Args:
        url: 要抓取和总结的网页URL
        target_ratio: 目标压缩比例，0.1-1.0之间
    
    Returns:
        网页内容总结
    """
    try:
        # 验证参数
        if not 0.1 <= target_ratio <= 1.0:
            return "错误: target_ratio 必须在 0.1 到 1.0 之间"
        
        ctx.info(f"开始抓取并总结网页: {url}")
        
        # 先抓取网页
        title, content = await scraper.scrape_url(url)
        
        # 然后总结
        full_content = f"网页标题: {title}\n\n{content}"
        summary = await summarizer.summarize_content(full_content, target_ratio)
        
        ctx.info("网页抓取和总结完成")
        return f"网页: {url}\n标题: {title}\n\n总结:\n{summary}"
        
    except Exception as e:
        logger.error(f"网页总结失败: {e}")
        return f"网页总结失败: {str(e)}"

src/fullscope_mcp_server/server.py:368-368 (registration)
The @mcp.tool() decorator registers the summarize_webpage function as an MCP tool.
```
@mcp.tool()
```

src/fullscope_mcp_server/server.py:369-379 (schema)

Function signature and docstring defining the input parameters (url: str, ctx: Context, target_ratio: float=0.2) and output (str), serving as the tool schema.

async def summarize_webpage(url: str, ctx: Context, target_ratio: float = 0.2) -> str:
    """
    抓取网页内容并总结为指定比例的长度（默认20%）
    
    Args:
        url: 要抓取和总结的网页URL
        target_ratio: 目标压缩比例，0.1-1.0之间
    
    Returns:
        网页内容总结
    """

src/fullscope_mcp_server/server.py:119-156 (helper)

WebScraper.scrape_url: Supporting function that fetches and parses the webpage HTML using httpx and BeautifulSoup, extracts title and cleans the text content.

async def scrape_url(self, url: str) -> tuple[str, str]:
    """
    抓取网页内容
    
    Args:
        url: 目标URL
        
    Returns:
        (title, content): 网页标题和清理后的文本内容
    """
    try:
        response = await self.session.get(url)
        response.raise_for_status()
        
        # 使用BeautifulSoup解析HTML
        soup = BeautifulSoup(response.text, 'html.parser')
        
        # 获取标题
        title = soup.find('title')
        title = title.get_text().strip() if title else "无标题"
        
        # 移除script和style标签
        for script in soup(["script", "style"]):
            script.decompose()
        
        # 提取主要内容
        content = soup.get_text()
        
        # 清理文本
        lines = (line.strip() for line in content.splitlines())
        chunks = (phrase.strip() for line in lines for phrase in line.split("  "))
        content = ' '.join(chunk for chunk in chunks if chunk)
        
        return title, content
        
    except Exception as e:
        logger.error(f"网页抓取失败 {url}: {e}")
        raise Exception(f"无法抓取网页: {str(e)}")

src/fullscope_mcp_server/server.py:57-106 (helper)

ContentSummarizer.summarize_content: Supporting function that uses OpenAI-compatible API (MiniMax) to summarize the provided content based on target ratio, with custom prompt option.

    async def summarize_content(self, content: str, target_ratio: float = 0.2, 
                              custom_prompt: str = None) -> str:
        """
        使用大模型总结内容
        
        Args:
            content: 要总结的内容
            target_ratio: 目标压缩比例 (默认20%)
            custom_prompt: 自定义总结提示词
        
        Returns:
            总结后的内容
        """
        try:
            # 检查内容长度，避免超出限制
            if len(content) > MAX_INPUT_TOKENS * 3:  # 粗略估算token
                content = content[:MAX_INPUT_TOKENS * 3]
                logger.warning("内容过长，已截断")
            
            # 构建总结提示词
            if custom_prompt:
                prompt = custom_prompt
            else:
                target_length = min(max(int(len(content) * target_ratio), 100), 1000)

                prompt = f"""请将以下内容总结为约{target_length}字的精炼版本，保留核心信息和关键要点：

{content}

总结要求：
1. 保持原文的主要观点和逻辑结构
2. 去除冗余和次要信息
3. 使用简洁明了的语言
4. 确保信息的准确性和完整性"""

            response = self.client.chat.completions.create(
                model=OPENAI_MODEL,
                messages=[
                    {"role": "system", "content": "你是一个专业的内容总结专家，擅长将长文本压缩为精炼的摘要。"},
                    {"role": "user", "content": prompt}
                ],
                max_tokens=MAX_OUTPUT_TOKENS,
                temperature=0.1
            )
            
            return response.choices[0].message.content.strip()
            
        except Exception as e:
            logger.error(f"内容总结失败: {e}")
            return f"总结失败: {str(e)}"

FullScope-MCP