One Iceberg MCP Server, Seven Catalogs: What It Takes to Reach Each One
Shows how to build an MCP server with seven catalogs using Python for data pipelines.
Why this scored 49
every term, weightedEngagement gained per hour since the last capture, against the fastest item on its own source
Whether that velocity is itself speeding up, as a per-hour rate
How many independent communities are talking about the same entity
Decays to zero over 14 days
Subtracted once something is big and old — we rank what's next, not what's peaked
Weights are hand-tuned, not learned — we're calibrating them against realized trends as history accumulates. On a topic's first sighting there's no previous reading to compare against, so acceleration starts from a neutral prior rather than a measurement, and velocity falls back to engagement over its whole lifetime until a second reading exists. Full methodology
Outlook
low confidence · estimate, not a guarantee7-day
~46
range 4–58
14-day
~46
range 2–61
30-day
~46
range 0–65
Signal history
7-day window (free)projected trajectory (estimate, not a guarantee)
Entities
Embed a live signal badge
[](https://www.signalcrest.app/topic/dev%3A4689759)
Drop this in a README or blog post — it updates automatically as the score moves.