News sentiment and volume data for AI

Understand how the news is covering any topic - and whether that coverage is positive or negative. Sentiment scores, media volume trends, and historical coverage data structured for AI analysis.

Tools for this workflow

`get_trends`

Chart news sentiment over time for any company or topic - see how media tone shifted around earnings, product launches, regulatory events, or crises.

get_trends(keyword='tesla', source='news sentiment', data_mode='weekly')

`get_growth`

Measure news sentiment trend alongside news volume - a topic gaining volume with declining sentiment signals a PR problem; rising volume with improving sentiment signals positive momentum.

get_growth(keyword='tesla', source='news sentiment, news volume', percent_growth=['3M', '6M'])

`get_ranked_trends`

Rank companies or topics by news sentiment growth - find which are seeing the most positive or most negative media narrative shift right now.

get_ranked_trends(source='news sentiment', sort='yoy_pct_change', limit=30)

`get_top_trends`

See what is leading in Google News RSS right now - no keyword needed. Captures the breaking stories driving media coverage across categories at this moment.

get_top_trends(type='Google News RSS', limit=25)

FAQ

Common questions

What news data does Trends MCP provide?

Two signals: news volume (how much coverage a topic is receiving) and news sentiment (whether that coverage skews positive, neutral, or negative). Both are normalized and returned as time series.

How is sentiment scored?

Sentiment is derived from NLP analysis of news article headlines and summaries, scored on a scale from -1 (strongly negative) to +1 (strongly positive). Trends MCP normalizes this to a 0-100 scale for consistency.

Can I track sentiment for a company over earnings periods?

Yes. Query a company name or ticker and the sentiment series will show how media tone shifted around earnings announcements, product launches, or regulatory events.

Which news sources are included?

Major English-language news outlets, financial media, and technology publications. The signal aggregates across sources rather than tracking individual outlets.

get_trends

get_growth

get_ranked_trends

get_top_trends

Common questions

Start building with live trend data

`get_trends`

`get_growth`

`get_ranked_trends`

`get_top_trends`