# Clairwave [Health: Active]

**Category:** 💻 Developer Tools  
**Repository:** https://github.com/clairwave/clairwave-mcp  
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**Directory Page:** https://allmcps.com/mcp/clairwave

## Description
Ocean acoustics: propagation models, bathymetry, sound speed, vessel noise, live AIS. Open.

## Claude Desktop Quick Installation
Remote MCP endpoint (confidence: high). Install path detected from listing signals. Add as a URL/SSE server in your client:

```json
"mcpServers": {
  "clairwave": {
    "url": "https://www.clairwave.com"
  }
}
```

## Documentation & README

# clairwave-mcp

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

[Clairwave](https://www.clairwave.com) 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](https://github.com/clairwave/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:** Settings → Connectors → *Create* (developer mode) → the URL above
- **Any MCP client:** point it at the URL; the server is stateless and JSON-response capable

## Tools

| Tool | What it does |
|---|---|
| `get_bathymetry` | Depth at a point, or a transect profile along a bearing |
| `get_sound_speed_profile` | Seasonal c(z) for a month + seabed parameters (cp, cs, density, attenuation, sediment) |
| `run_transmission_loss` | RAM parabolic-equation TL along a bearing; bathymetry/SSP/seabed fetched automatically; replication bundle included |
| `estimate_detection_range` | Sonar equation on a RAM run: continuous and furthest detection range, signal excess vs range |
| `run_bellhop_volume` | 3D Bellhop TL volume stored under a run id (uint8 cube + JSON sidecar links) |
| `vessel_source_level` | Ship radiated noise: broadband + third-octave spectrum + mechanism breakdown |
| `search_vessels` / `vessels_near` | Live AIS by name/MMSI, or within a radius of a point |
| `get_vessel` | Live position/track, particulars, and the 3D model (GLB, bow=+Z) with platform links |
| `get_vessel_photo` | Wikimedia Commons photo with attribution |
| `resolve_place` | Place name (port, strait, sea, 'off Halifax') → water coordinates; gazetteer + OpenStreetMap, snapped seaward off land |
| `habitat_received_level` | Power-summed vessel noise at a fixed site (fish farm, reef, hydrophone): live snapshot or 10-minute history series; top contributors |
| `about` | Models, data sources, limits |

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

```bash
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 (developer mode) and 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](https://github.com/clairwave/clairwave-mcp/blob/HEAD/PRIVACY.md). Terms: [TERMS.md](https://github.com/clairwave/clairwave-mcp/blob/HEAD/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.