MCP Hot News Server
A modern multi-platform hot news aggregation server based on FastMCP that supports real-time hot topics data collection from 13+ major platforms including Zhihu, Weibo, Baidu, and Bilibili.
README
MCP Hot News Server
一个基于 FastMCP 的现代化多平台热点新闻聚合服务器,支持实时获取各大平台热点数据。
A modern multi-platform hot news aggregation server based on FastMCP, supporting real-time hot topics data from major platforms.
✨ 特性 Features
- 🚀 基于 FastMCP:原生 MCP 协议支持,标准化的工具接口
- 🌐 多平台支持:知乎、微博、百度、哔哩哔哩、抖音等 13+ 平台
- ⚡ 智能缓存:TTL 缓存机制,提高响应速度
- 🔄 异步并发:高性能异步数据获取
- 📊 趋势分析:自动提取热门关键词和趋势话题
- 🛡️ 降级机制:API 失效时自动切换到模拟数据
- 🔧 LangChain 集成:完美适配 LangChain 工具生态
🚀 快速开始 Quick Start
安装 Installation
pip install mcp-hot-news
基础使用 Basic Usage
1. 启动 MCP 服务器
# 启动服务器(STDIO 模式)
mcp-hot-news
# 或者 HTTP 模式
mcp-hot-news --transport http --host 0.0.0.0 --port 8001
2. Python 代码调用
import asyncio
from mcp_hot_news.client import HotNewsClient
async def main():
async with HotNewsClient() as client:
# 获取微博热搜
weibo_news = await client.get_hot_news("weibo", limit=10)
print(weibo_news)
# 获取所有平台新闻
all_news = await client.get_all_platforms_news(limit=5)
print(all_news)
# 分析热点趋势
trends = await client.analyze_trends(limit=10)
print(trends)
asyncio.run(main())
3. LangChain 集成
from mcp_hot_news.langchain import HotNewsToolAdapter
from langchain.agents import initialize_agent
# 创建工具适配器
hot_news_tools = HotNewsToolAdapter()
# 获取 LangChain 工具
tools = await hot_news_tools.get_langchain_tools()
# 集成到 Agent
agent = initialize_agent(tools, llm, agent="zero-shot-react-description")
📋 支持的平台 Supported Platforms
| 平台 Platform | 支持状态 Status | API 来源 API Source |
|---|---|---|
| 知乎 Zhihu | ✅ | vvhan API |
| 微博 Weibo | ⚠️ | vvhan API (不稳定) |
| 百度 Baidu | ⚠️ | vvhan API (不稳定) |
| 哔哩哔哩 Bilibili | ✅ | vvhan API |
| 抖音 Douyin | ✅ | vvhan API |
| 快手 Kuaishou | ✅ | vvhan API |
| 今日头条 Toutiao | ✅ | vvhan API |
| 虎扑 Hupu | ⚠️ | vvhan API (不稳定) |
| 豆瓣 Douban | ✅ | vvhan API |
| IT之家 ITHome | ⚠️ | vvhan API (不稳定) |
⚠️ 注:部分平台 API 可能不稳定,会自动降级到模拟数据
🛠️ API 接口 API Reference
MCP 工具 MCP Tools
get_hot_news
获取指定平台的热点新闻
参数 Parameters:
platform(str): 平台名称limit(int): 获取数量,默认 20
get_all_platforms_news
获取所有平台的热点新闻汇总
参数 Parameters:
limit(int): 每个平台获取数量,默认 10
analyze_trends
分析当前热点趋势和关键词
参数 Parameters:
limit(int): 分析数量,默认 10
get_server_health
获取服务器健康状态
clear_cache
清空所有缓存数据
数据模型 Data Models
class NewsItem:
title: str # 新闻标题
url: str # 新闻链接
hot_value: Optional[Union[str, int]] # 热度值
rank: Optional[int] # 排名
platform: str # 平台名称
timestamp: str # 获取时间
class PlatformNews:
platform: str # 平台名称
news_list: List[NewsItem] # 新闻列表
update_time: str # 更新时间
total_count: int # 新闻总数
class TrendAnalysis:
hot_keywords: List[str] # 热门关键词
trending_topics: List[str] # 趋势话题
platform_summary: Dict[str, int] # 各平台热点数量
analysis_time: str # 分析时间
🔧 配置 Configuration
环境变量
# 缓存TTL(秒)
export MCP_CACHE_TTL=3600
# API请求超时(秒)
export MCP_REQUEST_TIMEOUT=10
# 日志级别
export MCP_LOG_LEVEL=INFO
自定义配置
from mcp_hot_news.server import HotNewsProvider
# 自定义配置
provider = HotNewsProvider()
provider.cache_manager.default_ttl = 7200 # 2小时缓存
🧪 开发和测试 Development & Testing
安装开发依赖
pip install -e ".[dev]"
运行测试
pytest
代码格式化
black src/ tests/
flake8 src/ tests/
mypy src/
📝 使用场景 Use Cases
- AI Agent 工具:为 LangChain/LangGraph Agent 提供实时热点数据
- 内容创作:获取热点话题进行内容创作
- 舆情监控:监控各平台热点趋势变化
- 数据分析:分析跨平台热点数据相关性
- API 服务:作为微服务提供热点数据接口
🤝 贡献 Contributing
欢迎贡献代码!请阅读 CONTRIBUTING.md 了解详细信息。
Welcome contributions! Please read CONTRIBUTING.md for details.
📄 许可证 License
MIT License - 详见 LICENSE 文件。
🙏 致谢 Acknowledgments
📞 联系我们 Contact
- GitHub Issues: 提交问题
- Email: wuzexiang@gmail.com
⭐ 如果这个项目对你有帮助,请给个 Star!
⭐ If this project helps you, please give it a Star!
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