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Track live global news signals with timelines, volume, tone, and surges.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "Geotone — Global News Signals" MCP server from askskill: Run: claude mcp add --transport http 'news-geotone-geotone' 'https://geotone.news/mcp'
Use Geotone to check the latest signals for a global breaking event. Show ranked coverage, the story timeline, and changes in volume and tone.
A ranked list of key coverage, the event timeline, and an overview of volume and tone shifts.
Use Geotone to track recent global news coverage of a brand, focusing on whether coverage has surged and how the overall tone has changed.
A trend summary of brand-related news, including coverage changes, tone, and notable surges.
Use Geotone to compare three global news topics by coverage intensity, timeline activity, and tone differences in a concise summary.
A comparison showing which topic is hotter, changing faster, or carrying stronger sentiment.
Researchers can use it to review ranked signals and story timelines for international events. This helps them quickly understand how a story develops and how coverage intensity changes.
Marketers can use it to watch global coverage volume, tone, and surges around a brand or topic. It is useful for spotting rising attention or shifts in media sentiment.
Data analysts can compare topics using coverage volume and tone changes. It is suitable for trend watching and prioritizing what matters most.
It provides live global news signals, including ranked wire coverage, story timelines, and changes in volume, tone, and surges to help users assess news dynamics quickly.
Based on the provided description, it is free and requires no authentication. For exact connection details, see the source repository.
From the description, it focuses on news signal monitoring—ranking, timelines, coverage volume, tone, and surges—rather than full article management. For more details, see the source repository.
Search global news events, track trending actors, and analyze sentiment trends.
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