Enables AI agents to verify claims against evidence through MCP tools, returning approved, rejected, or needs_review verdicts with replayable receipts.
This MCP server enables AI agents to extract, verify, and cache factual claims from text using Claude Haiku and semantic fingerprinting, with tools for content verification, signal verification, and fact memory search.
Enables AI agents to cross-verify candidate claims against caller-supplied source texts, flagging hallucinations, numerical drift, entity mismatches, contradictions, and unverified assertions. It returns sentence-level verdicts with matched evidence snippets and machine-readable factual grounding confidence scores, exposed over MCP stdio, HTTP REST, and A2A discovery routes.
Enables autonomous agents and MCP clients to decompose text into atomic claims and verify them against reference knowledge, detecting ungrounded claims, numerical contradictions, and hallucinated entities.
An MCP server that verifies whether a claim is actually supported by the source text at a given citation — independent of what the calling LLM asserts.