Global weather via Open-Meteo: forecast, historical, marine, air quality, geocoding, elevation.
One address for any MCP client. No sign-in needed on this server.
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Grouped by tool name. At most: creates or changes data: records, files, settings.
Odel charges nothing per call. The publisher may charge for its own service.
Geocode places, fetch global weather forecasts, historical climate, marine conditions, air quality, and terrain elevation via MCP. STDIO or Streamable HTTP.
Public Hosted Server: https://open-meteo.caseyjhand.com/mcp
Global weather from Open-Meteo: forecasts, history back to 1940, marine conditions, air quality, probabilistic ensembles, river discharge, and climate projections. Look up any place by name, pull hourly and daily variables, and run SQL over large results. No API key required.
| Tool | Description |
|---|---|
openmeteo_search_locations | Resolve a place name to ranked coordinates with country, region, timezone, and population |
openmeteo_get_forecast | Current conditions and hourly/daily forecast up to 16 days, with up to 92 past days, from best match or chosen models side by side |
openmeteo_get_historical | Hourly/daily history from the reanalysis archive, 1940 to present |
openmeteo_get_marine | Wave, swell, and sea-surface conditions: current, up to 8 forecast days, or an archive range, in metric or imperial units |
openmeteo_get_air_quality | Modeled CAMS pollutants, pollen, and AQI: current, up to 7 forecast days, or an archive range |
openmeteo_get_elevation | Copernicus DEM terrain elevation: up to 1,000 coordinate pairs, the first 100 sampled per call with the rest reported for resubmission |
openmeteo_get_ensemble | Per-member ensemble forecast (up to 64 members, up to 35 days) for exceedance and uncertainty |
openmeteo_get_flood | GloFAS river discharge: a ~6-month forecast or a date range from 1984, from seamless or chosen v4 models |
openmeteo_get_climate | Bias-corrected daily CMIP6 projections, 1950–2050, across up to 7 models |
openmeteo_dataframe_describe | List the tables and columns staged on a DataCanvas |
openmeteo_dataframe_query | Run a read-only SQL SELECT against staged tables |
openmeteo_dataframe_drop | Remove one staged table or view from a DataCanvas (opt-in) |
openmeteo_search_locations toolname ("Paris", not "Paris, France"), with optional country (ISO 3166-1 alpha-2) and language (default en); count 1–10, default 5timezone, country / country_code, admin1 / admin2, population, and feature_code; no match fails as no_resultsnotice flags a top match with null or sub-100,000 population, which often means a historic exonym ("Bangalore", "Calcutta")en is retried once in the language its script implies; effective_language names it when the retry succeeds (上海 → zh), and results come back localizedopenmeteo_get_forecast toolcurrent_variables, hourly_variables, or daily_variables (up to 50 each); forecast_days 1–16 (default 7), past_days 0–92 (default 0)hourly / daily records with hourly_units / daily_units; current_variables adds a current object from 15-minute data (interval 900) plus current_unitsmodels reads Open-Meteo best_match; models compares deterministic models (e.g. ncep_gfs_seamless, ecmwf_ifs025, dwd_icon_seamless; older spellings like gfs_seamless still resolve). With 2+ models each hourly and daily column carries a model-name suffix, and models is echoed. current_variables takes at most one model (current_multi_model)notice names it, or, when one model is left with unsuffixed columns, says the values cannot be attributed to a model; when every requested model misses, the call fails as coverage_gappast_days over openmeteo_get_historical for the last ~5 days, where the archive's ERA5 components lagopenmeteo_get_historical toolstart_date and end_date required (YYYY-MM-DD, from 1940-01-01), plus at least one of hourly_variables / daily_variables, named as on the forecast toolmodels reads Best Match (IFS HRES + ERA5 + ERA5-Land, source varies by date); up to 8 models pin a source. The ERA5 family runs ~5 days behind, ecmwf_ifs has no delay, and cerra covers Europe onlymodels and the returned date_range; with 2+ models each column carries a model-name suffix. A model with no data at the point (cerra outside Europe) is dropped from a multi-model response; the notice names it, or, when one model is left with unsuffixed columns (era5,cerra), says the values cannot be attributed to a modelopenmeteo_get_marine toolforecast_days 1–8 (upstream default 7) with past_days 0–92, or a start_date / end_date archive range back to at least 2022. Mixing them fails as forecast_window_conflict, a lone date as date_range_incompletecurrent_variables, hourly_variables, or daily_variables (wave height, period, and direction, swell, sea-surface temperature); sheltered water returns near-zero waves, a land point returns nulls (named in the notice), and ocean_current_velocity is null off the open oceancurrent_variables takes the hourly names and adds a current object from 15-minute data (interval 900) plus current_units, alongside either window; a daily name there fails as variable_wrong_cadencelength_unit (metric / imperial) sets every height, sea_level_height_msl included, in m or ft; wind_speed_unit (kmh, mph, ms, kn) sets ocean_current_velocity; temperature_unit (celsius / fahrenheit) sets sea_surface_temperature. Open-Meteo converts the values, and the *_units maps label them (mph reads mp/h)openmeteo_get_air_quality toolforecast_days 1–7 (upstream default 5) with past_days 0–92, or a start_date / end_date archive range from August 2022 (us_aqi starts a day later). Same forecast_window_conflict and date_range_incomplete rejections as the marine toolcurrent_variables (a current object, interval 3600) or hourly_variables: PM2.5, PM10, NO2, SO2, O3, CO, dust, pollen, European and US AQI. Pollen is modeled for Europe only, in pollen season; elsewhere it comes back null and the notice names itdata_source: "CAMS" marks every response as modeled grid data, not station measurementsopenmeteo_get_elevation toollatitudes[] / longitudes[] arrays of up to 1,000 pairs; unequal lengths fail as coordinate_count_mismatch, compared on the full arraysunprocessed_count says how many were left and next_offset is where to resume — resubmit latitudes.slice(next_offset) and longitudes.slice(next_offset) until next_offset is null. A call of 100 or fewer returns 0 / null. Each sampled pair counts as one call against Open-Meteo's per-IP limits (600 a minute), so a seventh 100-pair slice inside one minute comes back rate_limitedelevations[] in input order, each { latitude, longitude, elevation_m } from the Copernicus DEM (~90 m); elevation_m is null where the DEM has no value (latitude 90), without failing the rest of the callopenmeteo_get_ensemble toolhourly_variables / daily_variables; forecast_days 1–35 (default 7), past_days 0–92. Most models end within 16 days (ncep_gefs05 runs to about day 34); past that, columns are null and the notice says where data endsmodels takes one ensemble name (e.g. ecmwf_ifs025_ensemble, 51 members; gem_global_ensemble, 21); omitted or blank selects ecmwf_ifs025_ensemble, echoed in modeltemperature_2m_member01, …) across up to 64 members; member_count excludes the control run. A regional model queried outside its coverage fails as a non-retryable input error; switch to a global modelopenmeteo_get_flood tooldaily_variables required (up to 20), all in m³/s: river_discharge plus the statistics river_discharge_mean / _median / _min / _max / _p25 / _p75, which carry ensemble spread on forecast-run days and repeat river_discharge on reanalysis daysforecast_days 1–210 (the current GloFAS run reaches about six months; later days are null), or a start_date / end_date range from 1984-01-01. Mixing them fails as forecast_days_conflict, a lone date as date_range_incompletemodels reads seamless_v4: consolidated_v4 reanalysis before 2023-08-05, forecast_v4 runs from then on. models: ["consolidated_v4"] reads the reanalysis through 2025-05-31 (null after, and on forecast_days); forecast_v4 starts 2023-06-01. Output echoes models; with 2+ models each column carries a model-name suffix, and the notice names null spansopenmeteo_get_climate toolstart_date / end_date within 1950-01-01 to 2050-12-31 and daily_variables required (the API is daily-only); up to 7 CMIP6 models, e.g. CMCC_CM2_VHR4, MRI_AGCM3_2_Sopenmeteo_dataframe_describe toolcanvas_id a spilled weather tool returned; lists each table's name, kind, row_count, and columns (name, type, nullability), plus the canvas expires_atcanvas_not_enabled when canvas is off, or canvas_not_found when the ID is unknown or past its 24-hour sliding TTLopenmeteo_dataframe_query toolcanvas_id plus a read-only SELECT against the staged table_name; rows holds up to 100 rows, fewer when wide rows would pass the 80,000-character inline ceiling (values are never cut). row_count is the exact total; page with OFFSET <rows.length> under an ORDER BYrow_count is a lower bound, and count_error names the reason (e.g. count_timeout)canvas_not_enabled, canvas_not_found, missing_table, system_catalog_access (system catalogs are blocked), or row_too_large (the first row alone exceeds the ceiling: select fewer columns, or shorten values with left(), substr(), or list_slice())openmeteo_dataframe_drop toolOPENMETEO_DATAFRAME_DROP_ENABLED=truecanvas_id plus the exact table_name from openmeteo_dataframe_describe; removes that one table or view and returns dropped and the remaining_tables. A name that is not staged returns dropped: false, so a repeated drop is safecanvas_not_enabled, canvas_not_found, or invalid_table_name (not a plain SQL identifier, or a reserved keyword)Built on @cyanheads/mcp-ts-core: stdio and Streamable HTTP transports, pluggable auth (none / jwt / oauth), swappable storage (in-memory, filesystem, Supabase, Cloudflare KV/R2/D1), structured logging with optional OpenTelemetry tracing.
Open-Meteo-specific:
*_units maps, on the same variable names across forecast and archiveCANVAS_PROVIDER_TYPE=duckdb (the default) an over-budget result is staged as a DuckDB table (response carries canvas_id, table_name, truncated: true); with none it returns a bounded preview and truncated: truemodels on the forecast, historical, ensemble, climate, and flood tools is not an allowlist, so a model Open-Meteo adds later works without a server updateAgent-friendly output:
openmeteo_search_locations returns the IANA timezone alongside coordinates, ready for any weather tool's timezone input (default auto)variable_wrong_cadence (names the correct field), request_too_large (names the inputs to narrow), coverage_gap (a coordinate outside the dataset's grid or the model's domain), and rate_limited; only Too many concurrent requests is retried first. An outage that outlasts three attempts fails as upstream_unavailable, or upstream_timeout when the last attempt timed outnotice per response for what the data alone won't show: unserved variable names, nulls outside a dataset's coverage, and where spilled rows wentA public instance is available at https://open-meteo.caseyjhand.com/mcp — no installation required. Point any MCP client at it via Streamable HTTP:
{
"mcpServers": {
"open-meteo-mcp-server": {
"type": "streamable-http",
"url": "https://open-meteo.caseyjhand.com/mcp"
}
}
}
Add the following to your MCP client configuration file.
{
"mcpServers": {
"open-meteo-mcp-server": {
"type": "stdio",
"command": "bunx",
"args": ["@cyanheads/open-meteo-mcp-server@latest"],
"env": {
"MCP_TRANSPORT_TYPE": "stdio",
"MCP_LOG_LEVEL": "info"
}
}
}
}
Or with npx (no Bun required):
{
"mcpServers": {
"open-meteo-mcp-server": {
"type": "stdio",
"command": "npx",
"args": ["-y", "@cyanheads/open-meteo-mcp-server@latest"],
"env": {
"MCP_TRANSPORT_TYPE": "stdio",
"MCP_LOG_LEVEL": "info"
}
}
}
}
Or with Docker:
{
"mcpServers": {
"open-meteo-mcp-server": {
"type": "stdio",
"command": "docker",
"args": ["run", "-i", "--rm", "-e", "MCP_TRANSPORT_TYPE=stdio", "ghcr.io/cyanheads/open-meteo-mcp-server:latest"]
}
}
}
For Streamable HTTP, set the transport and start the server:
MCP_TRANSPORT_TYPE=http MCP_HTTP_PORT=3010 bun run start:http
# Server listens at http://localhost:3010/mcp
git clone https://github.com/cyanheads/open-meteo-mcp-server.git
cd open-meteo-mcp-server
bun install
Every variable is optional.
| Variable | Description | Default |
|---|---|---|
OPEN_METEO_API_BASE_URL | Forecast and elevation API base URL. | https://api.open-meteo.com |
OPEN_METEO_ARCHIVE_BASE_URL | Historical archive API base URL. | https://archive-api.open-meteo.com |
OPEN_METEO_MARINE_BASE_URL | Marine API base URL. | https://marine-api.open-meteo.com |
OPEN_METEO_AIR_QUALITY_BASE_URL | CAMS air quality API base URL. | https://air-quality-api.open-meteo.com |
OPEN_METEO_GEOCODING_BASE_URL | Geocoding API base URL. | https://geocoding-api.open-meteo.com |
OPEN_METEO_ENSEMBLE_BASE_URL | Ensemble API base URL. | https://ensemble-api.open-meteo.com |
OPEN_METEO_FLOOD_BASE_URL | GloFAS flood API base URL. | https://flood-api.open-meteo.com |
OPEN_METEO_CLIMATE_BASE_URL | CMIP6 climate API base URL. | https://climate-api.open-meteo.com |
CANVAS_PROVIDER_TYPE | duckdb stages over-budget weather results on a DataCanvas and enables the dataframe tools; none returns a bounded preview. | duckdb |
OPENMETEO_DATAFRAME_DROP_ENABLED | true makes openmeteo_dataframe_drop callable; otherwise it is listed as disabled. | false |
MCP_TRANSPORT_TYPE | Transport: stdio or http. | stdio |
MCP_HTTP_PORT | HTTP server port. | 3010 |
MCP_SESSION_MODE | HTTP session mode: stateless, stateful, or auto. | stateless |
MCP_AUTH_MODE | Authentication: none, jwt, or oauth. | none |
MCP_LOG_LEVEL | Log level (debug, info, notice, warning, error). | info |
LOGS_DIR | Directory for log files (Node.js only). | <project-root>/logs |
STORAGE_PROVIDER_TYPE | Storage backend: in-memory, filesystem, supabase, cloudflare-kv/r2/d1. | in-memory |
OTEL_ENABLED | Enable OpenTelemetry. | false |
See .env.example for the full list of optional overrides.
Build and run the production version:
# One-time build
bun run rebuild
# Run the built server
bun run start:http
# or
bun run start:stdio
Run checks and tests:
bun run devcheck # Lint, format, typecheck, security
bun run test # Vitest test suite
docker build -t open-meteo-mcp-server .
docker run --rm -p 3010:3010 open-meteo-mcp-server
The Dockerfile defaults to HTTP transport, stateless session mode, and logs to /var/log/open-meteo-mcp-server. OpenTelemetry peer dependencies are installed by default — build with --build-arg OTEL_ENABLED=false to omit them.
| Directory | Purpose |
|---|---|
src/index.ts | createApp() entry point — registers tools, initializes the Open-Meteo service and DataCanvas. |
src/config | Server-specific environment variable parsing and validation with Zod. |
src/mcp-server/tools/definitions | Tool definitions (*.tool.ts), one file per tool. |
src/mcp-server/tools | Shared tool helpers — model catalog, cadence validation, columnar reshape, spillover, response notices. |
src/services/open-meteo | HTTP client for the Open-Meteo APIs — retry, error classification, coverage-gap rejection. |
src/services/canvas-accessor.ts | DataCanvas accessor shared by the spill-capable tools. |
tests/ | Unit, integration, fuzz, and smoke tests. |
See CLAUDE.md for development guidelines and architectural rules. The short version:
try/catch in tool logicctx.log for request-scoped logging, ctx.state for tenant-scoped storagetools[] array in src/index.tsWeather data by Open-Meteo.com, licensed CC BY 4.0.
Issues are welcome. Run checks and tests before submitting:
bun run devcheck
bun run test
Apache-2.0 — see LICENSE for details.