Clairwave

clairwave-mcp

An open MCP server that gives AI assistants physically grounded ocean acoustics.

Clairwave runs validated propagation models (Bellhop, RAM/parabolic equation) on global bathymetry and seasonal sound-speed profiles, tracks live AIS vessels, and serves 3D hull models for them (shipshape). This server exposes that to Claude, ChatGPT, Gemini and any other MCP client — so an assistant reasoning about the ocean can run the physics instead of guessing.

Every result carries provenance (model, data source, run_id) and an open_url that opens the exact result in the platform. Simulation results include the bathymetry, sound-speed profile and bottom parameters that were used, so a researcher can replicate the run in MATLAB, Python or anything else.

Endpoint (no auth, no key): https://www.clairwave.com/mcp — Streamable HTTP.

Connect

• Claude Code: claude mcp add --transport http clairwave https://www.clairwave.com/mcp
• Claude.ai / Claude Desktop: Settings → Connectors → Add custom connector → the URL above
• ChatGPT: Plugins → search Clairwave → + (a listed plugin: no URL, no developer mode)
• Any MCP client: point it at the URL; the server is stateless and JSON-response capable

Tools

Typical latency against the live platform: bathymetry 0.5 s, SSP 6 s first time per 0.1° cell then cached, RAM transmission loss 1–3 s, detection range 1–3 s.

Run locally

pip install "mcp[cli]<2" httpx
python server.py            # streamable HTTP on :8890 (/mcp)
python server.py --stdio    # stdio for local clients
python tests/smoke_client.py

Environment: CLAIRWAVE_API, CLAIRWAVE_FLEET, CLAIRWAVE_SITE, MCP_PORT.

Where to find it

• Official MCP Registry: io.github.clairwave/clairwave (https://registry.modelcontextprotocol.io/v0.1/servers?search=io.github.clairwave/clairwave)
• Claude: Settings > Connectors > Add custom connector, URL https://www.clairwave.com/mcp, no auth.
• ChatGPT: listed in the Plugins directory as "Clairwave — Ocean acoustics & live ships"; search Clairwave and click +.
• Grok (grok.com/connectors > New > Custom): paste the same URL.
• xAI / OpenAI APIs: {"type": "mcp", "server_url": "https://www.clairwave.com/mcp", "server_label": "clairwave"}.

Place names

Every location tool takes either lat/lon or a place string. Names go through a maritime gazetteer first (ports resolve to their approaches, straits and seas to a representative water point; ~120 entries in gazetteer.py), then OpenStreetMap Nominatim. If the point is on land or shallower than 10 m it is walked seaward until it is deep enough, and the response's location block reports the original point, the snap distance and bearing, and the depth used. resolve_place exposes the same logic directly, with offshore_km to push a point further out.

Example prompts

• "What is the sound speed profile 50 km west of Gibraltar in March, and where is the sonic layer depth?"
• "How far could a 150 Hz, 170 dB source at 20 m depth be detected by a receiver at 100 m near 36N 5.5W, along bearing 090?"
• "Show transmission loss versus range at 200 Hz out to 30 km north of Halifax in winter."
• "What ships are within 15 km of the Strait of Hormuz right now, and how loud is the largest one?"
• "Run a 3D Bellhop volume at 400 Hz around 49.2N 123.3W and give me the link to open it."

Limits and support

• No sign-in. Compute calls share a platform-wide budget of about 20 per minute.
• Simulations are climatology-based (monthly sound speed, global bathymetry) and are not a substitute for in-situ measurements.
• Privacy policy: PRIVACY.md. Terms: TERMS.md. Support: contact@clairwave.com. Issues: https://github.com/clairwave/clairwave-mcp/issues

License

MIT. Data: AIS via the AISHub peer network (Clairwave contributes receivers); vessel photos CC-licensed with attribution; bathymetry and SSP sources cited in each response.