mcpField
N
News Sentiment API

News Sentiment API

Remote
trendsapi.aiData & Analytics0Updated 10w ago

About News Sentiment API

News Sentiment API provides time-series and growth data for news tone on a topic. It is for developers and analysts tracking changes in media sentiment, with Python and HTTP access.

Key features

  1. 01News sentiment time series
  2. 02Growth across preset or custom periods
  3. 03Python client and async client
  4. 04Pandas-compatible data handling

Use cases

  1. 01Track news tone around a company
  2. 02Compare sentiment across time windows

Configuration

Remote servers need no local install. Pick your client, then copy the config or install in one click.

Endpointhttps://news-sentiment.api.trendsapi.ai/mcp
Copy install command
Claude CodeTerminal
Cursor.cursor/mcp.json
VS Code.vscode/mcp.json
Claude Desktopclaude_desktop_config.json
Windsurf~/.codeium/windsurf/mcp_config.json

Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.

All endpoints
Streamable HTTPhttps://news-sentiment.api.trendsapi.ai/mcpAuth required

Tools

Details

From the project README

News sentiment API

News tone over time via the Trends API. Sentiment history and growth without scraping outlets.

License: MIT PyPI Python

Key: trendsapi.ai/#get-key. HTTP contract and every source: trendsapi-ai/trendsapi.

Authentication

pip install trendsapi-news-sentiment
export TRENDSAPI_KEY=your_key

Python 3.9+. Same key as the HTTP API.

from trendsapi_news_sentiment import TrendsAPI

client = TrendsAPI()                    # TRENDSAPI_KEY
# client = TrendsAPI(api_key="YOUR_KEY")

Keyword helpers default to source: "news sentiment". Pass source= to hit any other platform with the same client. Official full client (every source, no preset): trendsapi.

Methods

MethodREST modeReturns
get_time_series(keyword, source=, data_mode=)get_time_serieslist[TrendsDataPoint]
get_growth(keyword, percent_growth=, source=, data_mode=)get_growthGetGrowthResponse
get_top_trends(type=, ...)get_top_trendsGetTopTrendsResponse

source is lowercase (news sentiment). type is exact (Google Trends). Mixing them is a 400.

from trendsapi_news_sentiment import TrendsAPI

client = TrendsAPI()                    # TRENDSAPI_KEY
# client = TrendsAPI(api_key="YOUR_KEY")

series = client.get_time_series("nvidia")
print(series[-1].date, series[-1].value)

growth = client.get_growth("nvidia", percent_growth=["3M", "12M"])
print(growth.results[0].growth, growth.results[0].direction)

get_time_series

points = client.get_time_series("nvidia")

Each point:

FieldAlwaysMeaning
dateyesYYYY-MM-DD
valueyes0-100 index for this series
keywordyesEcho
volumenoAbsolute volume when available
source or datatypenoPipeline label

Python returns list[TrendsDataPoint]. Use .date and .value, not ["date"]. JS returns the same fields as object properties.

get_growth

g = client.get_growth("nvidia", percent_growth=["12M", "3M", "YTD"])
print(g.results[0].growth, g.results[0].direction)

percent_growth default: ["12M"]. Presets: 7D 14D 30D 1M 2M 3M 6M 9M 12M/1Y 18M 24M/2Y 36M/3Y 48M 60M/5Y MTD QTD YTD. Custom: {"name": "Launch", "recent": "2024-06-01", "baseline": "2024-01-01"}.

FieldMeaning
search_termKeyword
data_sourceSource
resultsOne object per window (period, growth, direction, dates, values)
metadataCounts / success flag

Several windows still count as one request. Python: growth.results[0].growth. JS: growth.results[0].growth.

Async

import asyncio
from trendsapi_news_sentiment import AsyncTrendsAPI

async def main():
    c = AsyncTrendsAPI()
    return await asyncio.gather(
        c.get_time_series("nvidia"),
        c.get_time_series("nvidia", source="google search"),
    )

asyncio.run(main())

Each 200 is one billed request.

Pandas

from dataclasses import asdict
import pandas as pd
from trendsapi_news_sentiment import TrendsAPI

df = pd.DataFrame(asdict(p) for p in TrendsAPI().get_time_series("nvidia"))
df["date"] = pd.to_datetime(df["date"])
print(df.set_index("date")["value"].resample("ME").mean().tail())

Call (curl)

FieldValue
EndpointPOST https://api.trendsapi.ai/api
AuthAuthorization: Bearer $TRENDSAPI_KEY
Historysource: news sentiment with get_time_series or get_growth
KeywordAny phrase, e.g. nvidia
Live typen/a
curl -sS -X POST https://api.trendsapi.ai/api \
  -H "Authorization: Bearer $TRENDSAPI_KEY" \
  -H "Content-Type: application/json" \
  --max-time 60 \
  -d '{"mode":"get_time_series","source":"news sentiment","keyword":"nvidia"}'

Source notes

  • Negative growth means tone fell vs the prior window, not that the company is negative.
  • Mention count is news-trends-api (source: news volume).
  • No per-article labels, no outlet breakdown.

Errors

HTTPClient
200Parsed payload. Python dataclasses / JS typed objects
400Raises. Fix source or type spelling
401Raises. Check TRENDSAPI_KEY
404Raises. No series for that keyword. Do not retry
429Raises. Quota
5xxClient retries, then raises

The HTTP body field is a JSON string. SDKs decode it. Raw curl must parse body a second time.

Site: https://trendsapi.ai/trends/news-sentiment.

License

MIT. See LICENSE.

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