NOAA Tides MCP Server

NOAA Tides MCP Server

The NOAA Tides MCP server bridges the gap between conversational AI assistants and real‑world oceanographic data by exposing NOAA CO-OPS (Center for Operational Oceanographic Products and Services) services through the Model Context Protocol. Developers can now ask an AI assistant for precise tide information, water level measurements, or station metadata without leaving the chat interface. This eliminates the need for manual API calls, complex authentication handling, and data parsing—streamlining workflows that depend on up‑to‑date tidal forecasts.

At its core, the server offers three high‑level tools:

• retrieves historical or real‑time water level records for a specified station, allowing users to query specific date ranges and adjust units or datum.
• provides forecasted high and low tide times, supporting custom intervals such as every 6 hours or the standard “hilo” high/low schedule.
• returns descriptive metadata for a station, including location, elevation, and data availability.

Each tool accepts straightforward parameters (station ID, dates, datum, time zone, units), mirroring the underlying CO-OPS API but wrapped in a clean, declarative interface. The server automatically handles HTTP requests to NOAA’s endpoints, parses the XML/JSON responses, and returns structured data ready for consumption by an assistant. This abstraction lets developers focus on higher‑level logic—such as recommending safe launch windows for boats or generating educational content about coastal dynamics—rather than on API plumbing.

Typical use cases include:

• Maritime logistics: A shipping assistant can schedule departures based on predicted tide heights.
• Coastal planning: Urban planners or environmental scientists can integrate tide data into risk assessments for flood zones.
• Education and outreach: Teachers can create interactive lessons where students ask an AI about local tide patterns.

Integration into AI workflows is seamless: a client simply declares the desired tool and its parameters, and the MCP runtime forwards the request to the server. The assistant then receives a structured response that can be directly displayed or further processed. Because the MCP server handles all network communication, developers avoid exposing sensitive credentials or managing rate limits within the assistant code.

What sets this MCP apart is its focused, domain‑specific coverage of NOAA CO-OPS services. By providing a curated set of high‑value tools with clear, documented parameters, it empowers developers to embed authoritative tidal data into AI experiences quickly and reliably—without the overhead of maintaining separate API clients or parsing raw NOAA feeds.