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What is AQUAVIEW MCP?

AQUAVIEW MCP is a hosted Model Context Protocol server that gives any LLM agent direct, structured access to a unified catalog of 700,000+ oceanographic, atmospheric, and marine datasets drawn from 68 authoritative sources — NOAA, all 11 IOOS Regional Associations, the World Ocean Database, the Global Argo array, GOES-R satellites, NEXRAD weather radar, ESA Sentinel, IFREMER, EMODnet, Ocean Networks Canada, and more.

Ask in plain English. AQUAVIEW finds, filters, aggregates, and returns the data — including direct download links to NetCDF, GRIB2, GeoTIFF, and CSV files where they exist.

"Find me all NDBC buoys in the Gulf of Mexico that recorded wave heights over 6 meters during Hurricane Ian in September 2022, and give me their data files."

The model uses AQUAVIEW's tools to scope by collection, bounding box, and time, apply CQL2 filters on per-variable statistics, and stream back STAC items with assets.

Install in 30 seconds

The AQUAVIEW MCP server is hosted at https://mcp.aquaview.org/mcp (HTTP transport). No installation. No keys.

Claude Code

claude mcp add --transport http aquaview https://mcp.aquaview.org/mcp

Claude Desktop

Settings → Developer → Edit Config and merge:

{
  "mcpServers": {
    "aquaview": {
      "type": "http",
      "url": "https://mcp.aquaview.org/mcp"
    }
  }
}

Cursor

Settings → MCP → Add new MCP Server, paste the URL above, type http.

ChatGPT, Gemini, OpenAI Agents SDK, Anthropic API direct, and more

See INSTALL.md for every supported client.

Try these prompts

Drop these into any MCP-enabled chat to see AQUAVIEW in action:

#	Prompt	Sources used
1	Show me sea surface temperature near the Florida Keys for the last 7 days.	COASTWATCH, NDBC, COOPS
2	Plot the track and intensity of Hurricane Ian using buoy and satellite data.	NDBC, GOES_R, NOAA_AOML_HDB
3	Find Argo float profiles within 200 km of Hawaii in March 2026 with min pressure under 10 dbar.	GADR
4	What's the current tide and storm surge forecast for Charleston, SC?	COOPS, NOS_COOPS
5	Map HF radar surface currents off the California coast right now.	IOOS_HFRADAR, CENCOOS, CALOOS
6	Give me all active glider missions in the Mid-Atlantic Bight.	IOOS, MARACOOS
7	How has Arctic sea-ice extent changed over the last 5 years?	POLARWATCH
8	List ROV dives by NOAA Okeanos Explorer with deep-sea video.	HYPERION, SEATUBE
9	Show me all oil-spill incident reports along the Gulf Coast since 2020.	INCIDENT_NEWS, NOAA_ORR
10	Vessel traffic density in the approaches to the Port of Long Beach.	MARINECADASTRE_AIS

Walkthroughs of each are in examples/.

Sources at a glance

68 collections, grouped. Full table with bbox/temporal coverage and variable lists in docs/collections.md.

Group	Collections
NOAA core	NOAA, NDBC, COOPS, NOS_COOPS, COOP, BATHYMETRY, DIGITALCOAST, MARINECADASTRE_AIS, INCIDENT_NEWS, NOAA_ORR, HYPERION
NOAA satellite & weather	GOES_R, HRRR, NEXRAD, NEXRAD_L2, COASTWATCH, COASTWATCH_CWCGOM, COASTWATCH_WC, POLARWATCH
NOAA labs & programs	PMEL, PMEL_GENERIC, GLERL, NOAA_GLERL, NOAA_AOML_HDB, NOAA_GDP, GADR, UAF, GOOS
NOAA NMFS fisheries	AFSC, NEFSC, NWFSC, PIFSC, SEFSC
IOOS Regional Associations	AOOS, CALOOS, CARICOOS, CDIP, CENCOOS, GLOS, IOOS, IOOS_HFRADAR, IOOS_OFFICE, IOOS_SENSORS, MARACOOS, NANOOS, NERACOOS, PacIOOS, SECOORA
International	APDRC, BCODM, CORIOLIS, IFREMER, EMODNET_PHYSICS, MARINE_IRELAND, SEATUBE, VOICE_OF_THE_OCEAN
Universities & research	OOI, OOI_GOLDCOPY, NWEM, SALISH_SEA_UBC, SPRAY, GCOOS_HIST, WOD
Global satellite imagery	sentinel-1-grd, sentinel-2-l2a, hls2-l30, esa-worldcover

Tools

AQUAVIEW exposes four MCP tools. Full schemas in docs/tools-reference.md.

Tool	Purpose
list_collections	Enumerate all 68 sources with bbox, temporal extent, keywords
search_datasets	Free-text + spatial + temporal + CQL2 search across the unified STAC catalog
aggregate	Counts, geohash heatmaps, per-collection breakdowns, datetime histograms
get_item	Fetch a single STAC item with full properties and asset download URLs

The catalog is built on the STAC specification, so items, properties, and assets follow a stable, well-documented schema.

Examples

Twenty-one walkthroughs in examples/, each a self-contained scenario with the prompt, a real transcript, the result, and variations to try.

Highlighted:

• 02-sea-surface-temperature/ — SST near a region using CoastWatch + WOD + buoys
• 03-hurricane-tracking/ — track + intensity from AOML, GOES-R, NDBC, GDP
• 05-argo-float-profiles/ — temperature/salinity profiles from the global Argo array

Notebooks

Three Jupyter notebooks in notebooks/ showing AQUAVIEW MCP through the native agent connectors of each major LLM provider:

• 01-claude-mcp-agent.ipynb — Anthropic Python SDK with mcp_servers parameter
• 02-chatgpt-mcp-agent.ipynb — OpenAI Agents SDK with hosted MCP tool
• 03-gemini-mcp-agent.ipynb — Google Gemini Agent SDK with MCP tool

Each notebook asks the same research question (Argo float profiles around Hawaii) so you can compare how each agent reasons over the same catalog.

How it works

   ┌─────────────────────────┐         ┌──────────────────────────┐
   │  Claude / ChatGPT /     │         │   AQUAVIEW MCP Server    │
   │  Gemini / Cursor /      │ ──HTTP─▶│   mcp.aquaview.org/mcp   │
   │  any MCP client         │         │                          │
   └─────────────────────────┘         │  list_collections        │
                                       │  search_datasets         │
                                       │  aggregate               │
                                       │  get_item                │
                                       └────────────┬─────────────┘
                                                    │
                                                    ▼
                              ┌──────────────────────────────────────┐
                              │  Unified STAC catalog (700K+ items)  │
                              │  spanning 68 collections             │
                              └──────────────────────────────────────┘
                                                    │
                  ┌────────────┬────────────────────┼────────────────────┬─────────────┐
                  ▼            ▼                    ▼                    ▼             ▼
              NOAA ERDDAP  IOOS RAs           World Ocean DB        Argo / GADR    Sentinel /
              CoastWatch   NDBC / CO-OPS      Global Drifter        OOI / IFREMER  GOES-R /
              GOES-R       MARACOOS, ...      Program (GDP)         EMODnet, ONC   NEXRAD, ...

The server speaks the STAC API under the hood. search_datasets compiles your natural-language scope into a CQL2 filter; aggregate runs server-side bucket queries so the LLM never has to fetch raw items just to count them.

Roadmap

• More example walkthroughs (target: 30+)
• Reference integrations: LangChain, LlamaIndex, AutoGen, Mastra
• Per-source quickstart pages
• A "build your own MCP-powered ocean app" tutorial

Contributing

Examples, prompt recipes, and integration guides are very welcome — see CONTRIBUTING.md. Bug reports and source-coverage requests go in Issues.

License

MIT © 2026 AQUAVIEW.

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_{Keywords: MCP server, Model Context Protocol, ocean data, atmospheric data, NOAA, NDBC, IOOS, World Ocean Database, Argo, GOES-R, NEXRAD, CoastWatch, ERDDAP, STAC, Claude, ChatGPT, Gemini, Grok, Cursor, AI agents, LLM tools, oceanography, climate data, marine data, satellite imagery, Sentinel.}