News Sentiment API - positive/negative tone trends as JSON

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

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());

The three modes

Why teams switch

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

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?

Every source on the same key

Live feeds (get_top_trends, no keyword needed)

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.

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.