Hot Topics MCP
Server Details
Trending topics from Weibo, Baidu, Zhihu & Google Trends for content and market research.
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- Status
- Unhealthy
- Uptime
- 53.8% over 22 days
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- jayniebingyu-cyber/hot-topics-mcp
- GitHub Stars
- 0
- Server Listing
- hot-topics-mcp
TDQS
Scored across 2 tools
The two tools are distinguishable by data source and region: get_reddit_intel pulls community threads from HN/StackExchange, while get_trending covers Chinese and US trend platforms. They do share a general 'hot topics' purpose, so an agent could briefly hesitate over which to call for a broad request, but the track lists and source descriptions clear up most ambiguity.
Both tool names use the get_ prefix, which establishes a consistent verb-led approach. get_reddit_intel follows a get_[source]_[result] pattern while get_trending is more of a get_[result] pattern, but the deviation is minor and the names remain predictable.
Two tools is a thin surface for a server claiming to cover 'hot topics.' The tools are broad in scope, so the count is not absurdly low, but one consolidated tool with source parameters could arguably express the same functionality.
For a read-only hot-topics research tool, the two tools cover the advertised sources (Reddit-style communities and major trend feeds from China/US). Minor gaps exist—no per-track detail endpoints or direct source history—but agents can work around these by calling the appropriate tool and filtering.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
2 tool updates
- First observed
get_reddit_intel - First observed
get_trending
Related MCP Connectors
Real-time trending from major Chinese platforms (Weibo, Douyin, Baidu, Zhihu).
Find rising topics before they peak across search and social. Free key at trendsapi.ai
Trending topics, cross-platform sentiment, viral content, community pulse & brand mentions.
Trend data from Google Trends, YouTube, TikTok, Reddit, Amazon, Wikipedia, npm, Steam and more
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