CLSTR

Track developing news stories

CLSTR gives your AI memory of the news. It reads over 100,000 articles a day from 40,000+ sources, groups every article about the same event into one deduplicated item, and links related events into "situations": ongoing storylines with a maintained summary and a full timeline.

What you can ask

What's developing in the world right now?
Example path

MCP connector

Server URL: https://mcp.clstr.news/mcp
Login: OAuth
Protocol: MCP 2025-06-18
Instructions: CLSTR gives an agent situational awareness of the news: multi-sourced, deduplicated synthesis instead of a stream of near-duplicate headlines. The pipeline reads over 100,000 articles a day from more than 40,000 sources in 170+ countries. Coverage of the same event is gathered across those sources and summarized before it surfaces, so what you get is the shape of the reporting, with a count of how many outlets are covering it and a significance score, rather than one outlet's headline in isolation.
CLSTR reports what sources are saying. It does not check whether they are right.
Two terms run through every tool:
Cluster: one real-world news event, assembled from many outlets covering the same happening and deduplicated into a single item (one event, not 20 versions of one headline). Each carries a source count (how many outlets are behind it) and a significance score generated by an AI model (1 to 10, where 8 and above is exceptional).
Situation (story arc): an ongoing storyline that groups related clusters over time. It keeps a maintained summary and a full chronological timeline, so you see not just what happened but how it developed. This is the memory: you can answer "what has happened here over the last six weeks", not just "what is the latest".
Which tool to use:
: find coverage by topic, entity, company, country, or event.
: what is developing right now, optionally within a category and a time window (24h, 7d, 30d).

Tools

Reads data4

Skills

None in the store listings or on the server

MCP connector

Server URL

https://mcp.clstr.news/mcp

OAuth

Protocol

MCP 2025-06-18

Instructions

CLSTR gives an agent situational awareness of the news: multi-sourced, deduplicated synthesis instead of a stream of near-duplicate headlines. The pipeline reads over 100,000 articles a day from more than 40,000 sources in 170+ countries. Coverage of the same event is gathered across those sources and summarized before it surfaces, so what you get is the shape of the reporting, with a count of how many outlets are covering it and a significance score, rather than one outlet's headline in isolation.

CLSTR reports what sources are saying. It does not check whether they are right.

Two terms run through every tool:

Cluster: one real-world news event, assembled from many outlets covering the same happening and deduplicated into a single item (one event, not 20 versions of one headline). Each carries a source count (how many outlets are behind it) and a significance score generated by an AI model (1 to 10, where 8 and above is exceptional).

Situation (story arc): an ongoing storyline that groups related clusters over time. It keeps a maintained summary and a full chronological timeline, so you see not just what happened but how it developed. This is the memory: you can answer "what has happened here over the last six weeks", not just "what is the latest".

Which tool to use:

: find coverage by topic, entity, company, country, or event.

: what is developing right now, optionally within a category and a time window (24h, 7d, 30d).