Article presents source verifier for AI agents using MCP

An article published on Hugging Face presents ProvenanceGuard, a post-generation verification layer for AI agents based on the Model Context Protocol (MCP). The system aims to detect “cross-source conflation”: cases in which a claim is supported by the combined evidence but attributed in the answer to the wrong source, a problem conventional verifiers may miss when they analyze all evidence together.

ProvenanceGuard processes MCP traces, preserves source identifiers, breaks the answer into claims, checks which source supports each one, and compares that source with the one named or implied by the answer. It then produces per-claim results and an overall decision to allow or block the text; blocked answers can go through repair and another verification pass. In the experiments described in the article, local models were used to find relevant sources, check textual support, and decompose answers, with additional checks for numbers, dates, and identifiers.