AI agents and RAG
Ground your agent in today's news.
Research
Measure attention, compare countries and track issues across a multi-year archive, tagged the same way for each source.
Turn a research question into filters, then collect the results.
Academics, policy teams and data scientists.
Labels are assigned the same way for each source.
Objectives
0/3Study framing and agenda setting across outlets.
Follow regulation and public figures in the news.
Measure media attention on a company or sector.
Build labelled datasets for NLP models.
One article
BloombergWorld news about one region, from outlets based in the US.
Illustrative scenario
A policy team pulls world news about Saudi Arabia and Turkey from US-based outlets, pages through the date range, and compares topics by country.
At a glance
curl -G https://api.newsmesh.co/v1/latest \ -d apiKey=$NEWSMESH_API_KEY \ -d category=world \ -d country=sa,tr \ -d sourceCountry=us \ -d limit=50
import os, requestsr = requests.get( "https://api.newsmesh.co/v1/latest", params={ "apiKey": os.environ["NEWSMESH_API_KEY"], "category": "world", "country": "sa,tr", "sourceCountry": "us", "limit": "50", },)articles = r.json()["data"]
const params = new URLSearchParams({ apiKey: process.env.NEWSMESH_API_KEY, category: "world", country: "sa,tr", sourceCountry: "us", limit: "50",});const res = await fetch(`https://api.newsmesh.co/v1/latest?${params}`);const { data } = await res.json();
{
"data": [{
"article_id": "eeebfd2ef935042c0d0005e5948712b7",
"title": "Saudi Says International Community Must Deal With Houthi Th…",
"source": "Bloomberg",
"category": "world",
"topics": ["international relations", "Houthi threat"],
"people": ["Faisal bin Farhan Al Saud"],
"country_relevance": ["Saudi Arabia"],
"link": "https://www.bloomberg.com/news/articles/2026-09-24/…"
}],
"next_cursor": "eyJwIjoi…"
}