MeteoSwiss Open Data — Python API, CLI & MCP server · tabular as DataFrames/Parquet, gridded as xarray/Zarr
foehn downloads every MeteoSwiss OGD collection via the STAC API, converts CSV/TXT station data to Parquet with Polars, and opens gridded collections — NetCDF climate grids, GRIB2 forecasts, and ODIM radar composites — as xarray Datasets or Zarr stores. It can optionally ingest everything into Databricks Unity Catalog Delta tables on a daily schedule, and ships an MCP server so LLMs can query Swiss weather data directly.
Daily weather in Bern, powered by foehn's MCP server and MeteoSwiss open data.
Why foehn?
- 20+ collections in one command — weather stations, radar, hail maps, forecasts, climate scenarios, and more
- Tabular and gridded — CSV station data as Polars DataFrames or Parquet; NetCDF, GRIB2 and ODIM radar grids as xarray Datasets or Zarr stores
- MCP server for LLMs — give your favorite LLM live access to MeteoSwiss data with the MCP server
- Significantly smaller on disk — columnar Parquet with Zstandard compression vs. raw CSVs
- Incremental by default — only re-downloads files that changed since your last run, tracked via
_last_run.json - No Spark required locally — download + conversion uses Polars only; Spark is optional for Delta ingestion
- Ships a Declarative Automation Bundle — ready-to-deploy daily job and historical backfill, no pipeline config needed
Quick start
pip install foehn
foehn download
Recent data (Jan 1 to yesterday) is downloaded and converted to Parquet under ./data/meteoswiss/.
Installation
From PyPI:
pip install foehn
From source:
git clone https://github.com/kayhendriksen/foehn
cd foehn
pip install -e .
With extras:
pip install "foehn[databricks]" # PySpark + Delta
pip install "foehn[mcp]" # MCP server
pip install "foehn[grids]" # xarray + Zarr for all gridded data (NetCDF, GRIB2, radar)
Requires Python 3.11 or later.
Python API
import foehn
df = foehn.load("smn", station="BER", frequency="d")
Load data directly into Polars DataFrames, explore metadata, download to disk, and convert to Parquet — all from Python. See the full Python API documentation.
CLI
foehn download smn pollen
foehn load smn --station BER --frequency d
The CLI mirrors the Python API with subcommands for downloading, converting, loading, and inspecting metadata. See the full CLI documentation.
Gridded data
ds = foehn.open_dataset("surface_derived_grid", match="rhiresd") # NetCDF climate grid
ds = foehn.open_dataset("forecast_icon_ch1", match="202605231500-0-t_2m-ctrl") # one GRIB2 field
ds = foehn.open_dataset("radar_precip", match="cpc2613000000") # one radar composite
foehn.to_zarr("surface_derived_grid", match="rhiresd") # Zarr store
NetCDF climate grids/normals/scenarios, GRIB2 forecasts (ICON-CH1/CH2, KENDA), and HDF5/ODIM radar composites all open as xarray Datasets instead of DataFrames. One extra covers them: pip install "foehn[grids]". See the gridded data documentation.
MCP server
{
"mcpServers": {
"foehn": {
"command": "foehn",
"args": ["mcp"]
}
}
}
Give any MCP-compatible LLM live access to MeteoSwiss data. See the full MCP server documentation.
Documentation
| Collections | All 20+ MeteoSwiss datasets, categories, and time slice conventions |
| Python API | Loading data, metadata, downloading, and Parquet conversion |
| Gridded data | NetCDF grids as xarray Datasets and Zarr stores |
| CLI | All subcommands, flags, and environment variables |
| MCP Server | Setup, configuration, and available tools |
| Databricks Pipeline | Declarative Automation Bundle deployment |
Data sources
| STAC API | https://data.geo.admin.ch/api/stac/v1 |
| Documentation | https://opendatadocs.meteoswiss.ch |
| MeteoSwiss OGD | https://github.com/MeteoSwiss/opendata |
License
MIT
1 maintainer
Metadata
1 maintainer
Release files for foehn 0.4.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| foehn-0.4.0.tar.gz | 2.6 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| foehn-0.4.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 2.6 MB
Release files / foehn-0.4.0.tar.gz
| Download URL | foehn-0.4.0.tar.gz |
|---|---|
| Size | 2.6 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
daaa62e4e570bd40cb312dcbcb1fae8f84e852a006c5810380efdcccc843ff83
|
|
BLAKE2b-256 checksum How to use checksums |
39181cf69da0ad062e104212d85adccba79ed7a202a1e2725ceb3a92f4fa3d6b
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Aug 28, 2026.
Transparency logRelease files / foehn-0.4.0-py3-none-any.whl
| Download URL | foehn-0.4.0-py3-none-any.whl |
|---|---|
| Size | 60.9 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
40c85dbd1e044311eef82bbf5b65249c01930c5118d930785c1ce04eb35170eb
|
|
BLAKE2b-256 checksum How to use checksums |
242ed89f0b5497bd4fc3508c77627c86338e00c31342142efe7fe7181bb11b0e
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Aug 28, 2026.
Transparency log
