Use cases
AI agent grounding (MCP)
An agent acting on a black-box reputation score can't tell "no data" from "known clean" — and that gap is a prompt-injection surface. WhisperGraph grounds the agent in live internet infrastructure over MCP, so it reasons from the actual graph: the resolutions, the routing, the feeds, the evidence.
Connect once, and the agent can pivot from a MITRE technique into real hosting the same way an analyst would.
Why this is hard without a graph
Autonomous investigation runtimes are only as good as what they can query. Hand an agent a reputation API and it inherits that API's blind spots — including its inability to say "I don't know." Flat lookups give the agent answers without the structure to reason about them.
What changes with WhisperGraph
Over MCP, the agent reads the same pre-joined graph an analyst does, with every layer linked and every result carrying its evidence. It can traverse, not just look up — and it can distinguish absence of data from a clean verdict. The workflows below show what that grounding makes possible.
1 workflow in AI agent grounding
Each one runs live on the graph — no signup.
AI / Agent Infrastructure Discovery
AI endpoints are becoming their own attack surface. This maps an organisation's externally visible AI and agent infrastructure — the API, model, and agent hosts exposed to the internet — from the outside, with no cooperation needed. A best-effort first look at an emerging and often unmanaged part of the footprint.