Ask any weather question in plain language. Get back more than a forecast — historical context, drawn from 35 years of ERA5 climate data, on whether conditions are normal, unusual, or record-breaking.
No AI-generated numbers. Every figure above comes from ERA5 reanalysis or live forecast data — a language model interprets your question, it never invents an answer.
The examples above are real, but they're fixed. This is the live app — ask about your own location and get the same kind of answer.
Opens the full app in place. For heavier use, see API access below.
A Telegram bot for quick questions and saved locations. Currently in development — not accepting new users yet.
The full experience — deeper comparisons, mapped locations, and the same app embedded above.
Programmatic access for agents, developers, and integrations. Structured, statistically rigorous, at volume.
Baseline publishes an MCP server so agents and AI tools can call it directly — no scraping, no prompting a model to guess at climate numbers. Every tool call returns structured, sourced data.
Ask a weather or climate question in plain language. Returns forecast plus full historical context — percentile rank and anomaly against the 35-year record.
Same as above, for an exact latitude/longitude instead of a place name — for agents working from coordinates directly.
Precipitation and temperature status since the start of the water year (Oct 1 US / Jan 1 elsewhere), ranked against 35 years.
How unusual current or forecast conditions are at a single location — the "does this matter" question, answered directly.
Rank 2–10 locations against each other by precipitation, temperature, or snowfall — or use a curated category like colorado_ski_resorts.
pip install baseline-mcp · endpoint api.baselinecontext.com — also listed on the MCP registry (Glama, PulseMCP)
Get an API key →
You'll get a working key immediately — no approval wait, no card required. This is early: expect some rough edges as we improve accuracy and coverage across locations and time windows.
If you hit something wrong or confusing, tell us. It directly shapes what we fix next — you're not just a user right now, you're helping build this.