wikipedia-trends-mcp
Related Servers
Alternatives to wikipedia-trends-mcp
No user-submitted related servers found.
Related Servers
- AlicenseNot gradedqualityCmaintenanceAn MCP server that exposes Wikipedia page view trends as clean JSON, providing normalized 0-100 trend scores, growth rates over 3M/6M/12M/5Y windows, and live most-viewed article feeds, comparable across 15 sources including Google, YouTube, and TikTok.MIT
- AlicenseNot gradedqualityBmaintenanceProvides Wikipedia page view trend data including spike detection, historical traffic, and cross-platform comparison, enabling AI to access a leading indicator of public curiosity.MIT
- AlicenseNot gradedqualityDmaintenanceMCP server providing live Wikipedia recent changes feed, page summaries, trending pages, and Wikidata entity lookup.MIT

Trends MCPofficial
AlicenseNot gradedqualityCmaintenanceProvides hosted trend data MCP server for querying Google, TikTok, Amazon, Reddit, YouTube, Steam, npm and 30+ trend sources in natural language from any MCP-compatible AI.MIT- AlicenseNot gradedqualityCmaintenanceMCP server providing news article mention volume data, weekly series, growth percentages, and a live Google News feed as an AI tool.20 PyPIMIT
- AlicenseNot gradedqualityBmaintenanceMCP server for trend-pulse, an agentic trend intelligence platform that fetches and analyzes trending topics from 37 sources, provides search, historical data, and lifecycle prediction via 29 tools.252 PyPI64MIT
TDQS
Scored across 3 tools
Each tool serves a clearly distinct purpose: get_growth for point-to-point changes, get_time_series for full history, and get_top_trends for live boards. The descriptions explicitly cross-reference each other to prevent misselection, leaving no ambiguity.
All three tools follow a consistent 'get_' prefix with a descriptive noun: get_growth, get_time_series, get_top_trends. This predictable pattern makes it easy for agents to infer functionality from names.
With only 3 tools, the server is tightly scoped but each tool addresses a fundamental need: growth, historical data, and current trends. This is a well-focused set that avoids redundancy.
The tools cover the main workflows for a trends service: analyzing growth, retrieving full time series for charting, and accessing live rankings. Edge cases like categories and rank changes are handled, leaving no obvious dead ends.