wikipedia-trends-mcp
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- 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
- FlicenseNot gradedqualityDmaintenanceMCP server providing live Wikipedia recent changes feed, page summaries, trending pages, and Wikidata entity lookup.-

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.MIT
- AlicenseNot gradedqualityCmaintenanceMCP 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.204 PyPI60MIT
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.