Skip to main content
Glama

Related Servers

Alternatives to windext

No user-submitted related servers found.

    Related Servers

    • A
      license
      A
      quality
      C
      maintenance
      MCP server for wind forecasts, live measurements, wave forecasts, and tides, enabling kite and surf spot checks via AI assistants.
      5
      8 npm
      MIT
    • A
      license
      Not graded
      quality
      A
      maintenance
      Enables any MCP-compatible assistant to plan sailing passages using wind and sea forecasts, with boat-specific polars, per-leg ETAs, complexity scores, and deep links to interactive plans. Works globally, with higher-resolution models over France, and supports multi-day departure window comparisons.
      11
      AGPL 3.0
    • A
      license
      Not graded
      quality
      A
      maintenance
      Enables querying and comparing operational numerical weather models, including global and regional, deterministic and ensemble, physics-based and AI forecasts, with a unified API.
      44 npm
      MIT

    TDQS

    A3.5/5.0

    Scored across 7 tools

    Disambiguation4/5

    Each tool targets a distinct capability (search, spot details, submission, forecast, riding windows, tides, model metadata), and the descriptions give clear sequencing cues like 'always call this first.' The main soft spot is find_spot vs spot_info, which both surface spot data, but the descriptions adequately separate search-by-name from a full card/radius lookup.

    Naming Consistency3/5

    Names are readable snake_case but mix conventions: verb_noun forms (find_spot, submit_spot, list_models) sit alongside noun-noun forms (spot_info, spot_forecast) and bare nouns (tides, ride_windows). A single consistent pattern like get_spot, get_forecast would be cleaner, though the domain theme keeps it understandable.

    Tool Count5/5

    Seven tools is well-scoped for a wind-forecast/spot database server. Each tool covers a distinct piece of the domain (discovery, detail, contribution, forecast, derived windows, tides, model info) with no filler.

    Completeness4/5

    The core lifecycle is covered: find spots, view details, submit/correct spots, get forecasts, derive ride windows, check tides, and inspect models. Minor gaps exist (no saved/favorite spots, user preferences for rider range, or alerts), but agents can work around these.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues