Ground agents in verifiable dog breed data — traits, size and lifespan — so pet answers rest on sourced facts instead of guesses.
Let an agent call Dog Breed to expand an ID into full, structured detail from live data — grounding enrichment steps in fact, not recall.
Wire dogbreeds into an agent so it pulls the fields it's missing at the moment it needs them, each traceable to the source.
Every detail the agent adds carries Dog Breed as its origin, keeping the pipeline verifiable.
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.
breedfoundCountfoundBreedsHow to ground an agent in it over MCP.