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Is DCL Trust Oracle — AI/LLM Output Audit (x402 MCP) reliable?

Being measured Measurement in progress: 1 check(s) so far. A verdict needs at least 3 checks.

En français : Mesure en cours. Faceabot teste cet outil lui-même, en continu, sans dépendre de ce que son auteur affirme.

What it does

AI/LLM agent output audit MCP: policy eval, tamper-evident chain, AI safety, x402 USDC on Base.

Source: official MCP registry (registry.modelcontextprotocol.io) · version 2.3.1 · publisher website
Connect your agent
{
  "mcpServers": {
    "dcl-trust-oracle": {
      "url": "https://mcp.fronesislabs.com/mcp"
    }
  }
}
Or ask Faceabot first: MCP tool check_reliability {"id":"com.fronesislabs/dcl-trust-oracle"} on https://faceabot.com/api/mcp.
Does it actually do the job?

Not tested with a real task yet. Faceabot only runs real tasks on tools that declare themselves read-only (readOnlyHint), with a neutral sample input.

Faceabot measurements
WhenAnswersReal taskLatency
2026-10-06 13:46 UTC❌ timeout8000 ms
Method: MCP initialize then tools/list from Faceabot (FaceabotProbe/1.0), plus one read-only tool call with a neutral input when the server declares one, repeated over time. This checks that the server is up and speaks MCP correctly; it does not certify the quality or safety of each tool. How measurement works.

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Publisher of DCL Trust Oracle — AI/LLM Output Audit (x402 MCP)?

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