ERA5 SMI
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
| logging | {} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| extensions | {
"io.modelcontextprotocol/ui": {}
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| inspect_netcdfA | Inspects a NetCDF file and returns a summary of its contents (dimensions, variables, coordinates). |
| fetch_era5_pressure_levelsA | Downloads ERA5 monthly mean data on specific pressure levels for a given month across one or more years. |
| fetch_era5_single_levelsB | Downloads ERA5 monthly mean surface data. |
| fetch_era5_hourly_single_levelsB | Downloads ERA5 hourly surface data. |
| fetch_era5_hourly_pressure_levelsB | Downloads ERA5 hourly data on specific pressure levels. |
| fetch_era5_land_soil_moistureA | Downloads ERA5-Land monthly mean volumetric soil water content for one soil layer. This is the primary data source for the SMI pipeline (see skills/calculate-smi). |
| extract_point_timeseriesA | Extracts the nearest-pixel monthly time series from a downloaded NetCDF
file and writes it as a CSV with columns year,month,date,.
This CSV is the expected input format for the |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 7 tools
Each tool targets a distinct data source or processing step: inspect_netcdf for inspection, the fetch tools are differentiated by time resolution (hourly vs monthly mean) and data type (pressure levels, single levels, land soil moisture), and extract_point_timeseries is the only output-writing tool. There is no meaningful overlap between tool purposes.
The naming follows a consistent snake_case verb_noun pattern, with fetch_era5_* clearly grouped by data type and time resolution. Minor deviation: tools without 'hourly' are implicitly monthly mean (e.g., fetch_era5_pressure_levels), which is not explicitly reflected in the name, and inspect/extract use generic verbs rather than the fetch_ prefix.
Seven tools cover the full data-preparation workflow for the ERA5 SMI pipeline: inspection, downloading multiple ERA5 variants, and extracting point timeseries. The count is well-scoped, not bloated or sparse, and each tool has a clear role.
The tool surface covers the main data types (pressure levels, single levels, land soil moisture) in both hourly and monthly resolutions, plus inspection and extraction. Minor gaps: there is no tool for directly listing available variables or fetching ERA5-Land hourly soil moisture, but these are not critical given the stated SMI focus.