HotNews MCP Server
by MCP-Mirror
This is a Model Context Protocol (MCP) server that provides real-time hot trending topics from major Chinese social platforms and news sites. It allows easy integration with AI models.
Last updated: N/A
What is HotNews MCP Server?
The HotNews MCP Server is a service that aggregates real-time trending topics from nine major Chinese social media and news platforms. It is designed to be compatible with the Model Context Protocol (MCP), enabling easy integration with AI models for context-aware applications.
How to use HotNews MCP Server?
The server can be installed and run using NPX or Docker. To retrieve hot topics, use the get_hot_news
tool with a list of platform IDs as arguments. For example, get_hot_news([1,3,7])
retrieves hot lists from Zhihu, Baidu, and Hupu.
Key features of HotNews MCP Server
Real-time hot topics from 9 major Chinese platforms
MCP protocol compatible
Easy integration with AI models
Markdown formatted output with clickable links
Heat index support (where available)
Use cases of HotNews MCP Server
AI-powered news summarization
Sentiment analysis of trending topics
Contextual understanding for chatbots
Trend monitoring and analysis
FAQ from HotNews MCP Server
What platforms are supported?
What platforms are supported?
The server supports Zhihu, 36Kr, Baidu, Bilibili, Weibo, Douyin, Hupu, Douban, and IT News.
How do I install the server?
How do I install the server?
You can install it using NPX or Docker. Refer to the Installation section in the README for detailed instructions.
What is the API source?
What is the API source?
This project uses the api.vvhan.com
service for fetching hot topics data.
How do I get hot news from a specific platform?
How do I get hot news from a specific platform?
Use the get_hot_news
tool with the corresponding platform ID. For example, get_hot_news([3])
retrieves hot news from Baidu.
Is there a Docker image available?
Is there a Docker image available?
Yes, but the Docker image is not uploaded to Docker Hub, so you need to build it yourself using the provided Dockerfile.