News Sentiment API

License: MIT API v1 MCP compatible Free tier

News sentiment as clean JSON: positive/negative tone scores for any topic over time, with growth windows and volume context from one REST endpoint. NLP already done - you get a number, not a corpus.

One endpoint. One API key. One normalized 0-100 trend score you can compare against 14 other platforms.

Docs: https://trendsapi.ai/#quickstart · llms.txt: https://trendsapi.ai/llms.txt · Free API key (100 req/mo): https://trendsapi.ai/#get-key

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What a call looks like

curl -X POST https://api.trendsapi.ai/api \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"mode": "get_growth", "source": "news sentiment", "keyword": "tesla", "percent_growth": ["3M", "12M"]}'

{
  "keyword": "tesla",
  "source": "news sentiment",
  "growth": { "3M": 41.8, "12M": 212.4 },
  "timestamp": "2026-08-03T12:00:00Z"
}

Quickstart (60 seconds)

1. Get a free API key at https://trendsapi.ai/#get-key - 100 requests/month, no credit card.

2. Make your first call:

curl -X POST https://api.trendsapi.ai/api \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"mode": "get_time_series", "source": "news sentiment", "keyword": "tesla"}'

Python:

import requests

res = requests.post(
    "https://api.trendsapi.ai/api",
    headers={"Authorization": "Bearer YOUR_API_KEY"},
    json={"mode": "get_growth", "source": "news sentiment", "keyword": "tesla",
          "percent_growth": ["3M", "12M"]},
)
print(res.json())

Node.js:

const res = await fetch("https://api.trendsapi.ai/api", {
  method: "POST",
  headers: {
    Authorization: "Bearer YOUR_API_KEY",
    "Content-Type": "application/json",
  },
  body: JSON.stringify({ mode: "get_growth", source: "news sentiment", keyword: "tesla",
                          percent_growth: ["3M", "12M"] }),
});
console.log(await res.json());

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The three modes

Mode	What it returns	Needs a keyword?
get_time_series	Historical sentiment score as a normalized 0-100 series	yes
get_growth	Growth % over 3M / 6M / 12M / 5Y windows	yes
get_top_trends	Live trending feeds (21 of them)	no

Why teams switch

	DIY sentiment pipeline	Trends API
NLP pipeline	build and maintain your own	pre-computed scores
Output	raw articles to classify	one score per period
History	store it yourself	weekly/daily series included
Cross-signal compare	no	same scale as volume, search, social
Free tier	n/a	100 requests/month

Use cases

• Equity research: sentiment shifts on a ticker often precede price moves
• Brand management: catch negative tone trends before they become crises
• Product launches: measure whether coverage skewed positive after launch week
• Policy and macro: track tone around regulation, rates, or sectors

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Use it from your AI assistant (MCP)

The same API key powers the Trends API MCP server, so Claude, Cursor, VS Code, ChatGPT and any MCP-compatible client can query this data in natural language.

+ Add to Cursor (one click)

Cursor / Windsurf / Cline (~/.cursor/mcp.json or equivalent):

{
  "mcpServers": {
    "trendsapi": {
      "url": "https://api.trendsapi.ai/mcp",
      "transport": "http",
      "headers": { "Authorization": "Bearer YOUR_API_KEY" }
    }
  }
}

VS Code / GitHub Copilot (.vscode/mcp.json):

{
  "servers": {
    "trendsapi": {
      "type": "http",
      "url": "https://api.trendsapi.ai/mcp",
      "headers": { "Authorization": "Bearer YOUR_API_KEY" }
    }
  }
}

Claude Desktop (claude_desktop_config.json):

{
  "mcpServers": {
    "trendsapi": {
      "command": "npx",
      "args": ["-y", "mcp-remote", "https://api.trendsapi.ai/mcp", "--header", "Authorization:${AUTH_HEADER}"],
      "env": { "AUTH_HEADER": "Bearer YOUR_API_KEY" }
    }
  }
}

Claude.ai (browser): Settings -> Connectors -> Add custom connector -> https://api.trendsapi.ai/mcp

Then ask things like:

How did "creatine gummies" grow on TikTok vs Google over the last 12 months?
What is trending on YouTube right now?

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Every source on the same key

Source	source value	What it measures
Google Search	google search	Search volume
Google Images	google images	Image search volume
Google News	google news	News search volume
Google Shopping	google shopping	Shopping search volume
YouTube	youtube	Search volume
TikTok	tiktok	Hashtag volume
Reddit	reddit	Subreddit subscribers
Amazon	amazon	Product search volume
Wikipedia	wikipedia	Page views
News volume	news volume	Article mention volume
News sentiment	news sentiment	Positive / negative score
App downloads	app downloads	Android downloads (AppBrain)
App rankings	app rankings	Android chart position
npm	npm	Weekly package downloads
Steam	steam	Concurrent players (monthly)

Live feeds (get_top_trends, no keyword needed)

Feed	type value
Google Trends	Google Trends
Google News Top News	Google News Top News
TikTok Trending Hashtags	TikTok Trending Hashtags
TikTok Trending Searches	TikTok Trending Searches
TikTok Shop Hot Products	TikTok Shop Hot Products
YouTube Trending	YouTube Trending
X (Twitter) Trending	X (Twitter) Trending
Reddit Hot Posts	Reddit Hot Posts
Reddit World News	Reddit World News
Wikipedia Trending	Wikipedia Trending
Amazon Best Sellers Top Rated	Amazon Best Sellers Top Rated
Amazon Best Sellers by Category	Amazon Best Sellers by Category
App Store Top Free	App Store Top Free
App Store Top Paid	App Store Top Paid
Google Play	Google Play
Top Websites	Top Websites
Spotify Top Podcasts	Spotify Top Podcasts
Steam Most Played	Steam Most Played
GitHub Trending Repos	GitHub Trending Repos
IMDb MOVIEmeter	IMDb MOVIEmeter
Open Library Trending Books	Open Library Trending Books

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FAQ

What news sentiment data does Trends API provide?

A positive/negative sentiment score for any topic as a time series (weekly or daily), plus growth windows showing how tone is shifting. Pair it with the news volume source to see tone and attention together.

How is sentiment computed?

Articles mentioning your keyword are classified for tone, then aggregated into a normalized score per period. You get the number - no corpus handling, no model hosting.

Can I combine sentiment with mention volume?

Yes, and you should: rising negative sentiment on rising volume is a very different signal than rising negative sentiment on falling volume. Both sources come back in the same response shape.

How far back does history go?

Up to 5 years on paid plans; 90 days on the free tier.

Is this financial advice-grade data?

It is an alternative-data input used in research workflows. Like any sentiment signal, treat it as one input among many, not a trading system by itself.

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Links

• Docs & quickstart: https://trendsapi.ai/#quickstart
• llms.txt (machine-readable API reference): https://trendsapi.ai/llms.txt
• Pricing (free tier: 100 requests/month): https://trendsapi.ai/#pricing
• Get an API key: https://trendsapi.ai/#get-key

License

MIT - see LICENSE. Data is served by Trends API; usage of the API itself is subject to the plan limits on your key.