Ground agents in verifiable land-versus-ocean classification for any coordinate, so geospatial answers rest on real geography instead of inference.
Give an agent Land-or-Sea so it resolves places, distances, and timezones from real data instead of approximating — the difference between a plausible answer and a correct one.
When a user names a location, the agent calls coordinatesaresea to confirm and normalize it before acting, closing off a common source of silent errors.
Every location fact the agent uses carries Land-or-Sea as its origin, so the reasoning is auditable end to end.
Point your agent framework at the VerveContext endpoint. Every enabled source — this one included — becomes a tool the model can call. No per-source plumbing.
{
"mcpServers": {
"vervecontext": {
"url": "https://api.vervecontext.com/v1/mcp",
"headers": { "x-api-key": "vc_live_••••" }
}
}
}Each call returns structured fields your agent can read — and trace back to this source.
latitudelongitudeisSeaHow to ground an agent in it over MCP.