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

DCL Trust Oracle

Don't trust the agent. Trust the proof.

Autonomous AI agents now take actions with real consequences — financial, legal, reputational. Most of them are black boxes: no record of what was decided, why, or whether that decision was tampered with afterward.

DCL Trust Oracle closes that gap. Every agent output is evaluated against policy in real time and sealed into a tamper-evident hash chain — a deterministic, cryptographically verifiable record of what happened and when. Edit any past entry and the entire chain invalidates. No one — not even Fronesis Labs — has to be trusted for the record to hold up.

What It Does

DCL Trust Oracle provides deterministic policy evaluation for LLM outputs with a tamper-evident audit chain. The system stores only cryptographic hashes and decision metadata — never raw content — enabling verifiable, post-action forensic analysis across distributed AI agents.

Available two ways:

• REST API (webhook_server.py) — direct HTTP integration.
• MCP Server (mcp_server.py) — native Model Context Protocol integration for AI agents. Live at https://mcp.fronesislabs.com/mcp (streamable-http). Also listed on Smithery (remote URL → same production endpoint; see smithery.yaml) and the official MCP Registry.

Both servers share the same evaluation logic and tamper-evident chain (dcl_core.py), and are priced identically.

Quick Start

REST API

pip install -r requirements.txt

python webhook_server.py

Server runs on `http://localhost:8080`

MCP Server

Production (hosted):

https://mcp.fronesislabs.com/mcp

Streamable HTTP transport — point any MCP client here directly, no setup required.

Local development:

pip install -r requirements.txt

python mcp_server.py

Server runs on `http://localhost:8081` (streamable-http transport)

Tools & Endpoints

Pre-Action Evaluation

Catch a bad output *before* it reaches a user, a wallet, or downstream system.

Session Management

Post-Action Forensics

When something *did* go wrong, reconstruct exactly what happened.

Post-Action Scans

DCL Update Sentinel (Continuous Skill Monitoring)

Continuous security auditing and release verification for AI Agent Skills and GitHub repositories. Sentinel monitors code updates via GitHub Webhooks, blocks regressions against your security baseline, and automatically recovers skill status upon clean rescans.

Key Features of Sentinel:

• Idempotent Webhook Processing: Built-in protection against duplicate GitHub delivery retries (X-GitHub-Delivery tracking).
• Auto-Recovery: Skills blocked due to security regressions (status: blocked) are automatically restored to active once a clean, policy-compliant release is published.
• Strict Owner Verification: Subscription renewals require cryptographic signature match with the registered owner's wallet (owner_payer_ref).
• Baseline Policy Gate: Registration requires a passing initial audit (score >= 0.80). Compromised or failing repositories are rejected immediately (HTTP 422) to prevent invalid entitlement setup.

Crypto & Trading Compliance (MCP only)

These tools are exposed on the live MCP server only (no REST routes in webhook_server.py).

Utility (free, REST only)

Example Response

{

"verdict": "COMMIT", "confidence": 0.95, "reason": "All policy checks passed", "tx_hash": "0x7a8f3b2c...", "chain_index": 42, "input_hash": "0x9d4e1f...", "policy_version": "1.0.0", "timestamp": 1721635200.123, "pipeline_id": "abc123", "drift_mode": "NORMAL", "drift_score": 0.15 }

Verifying the Chain Yourself

You don't have to take the server's word for it. tx_hash is recomputed from the record's own fields, not just linked to the previous row — so anyone can independently confirm a record wasn't edited after the fact, without calling back into this server. See @fronesis-labs/dcl-sdk (TS/JS) or dcl-core (Python) for the free, offline verification libraries.

Metering & Settlement

Every paid call above is metered and settled automatically via the x402 protocol (USDC on Base).

We support two payment models:

• Per-Call Micropayments ($0.01 – $0.50) for instant, on-demand evaluations.
• 30-Day Recurring Entitlements ($49.00) for continuous skill monitoring via DCL Update Sentinel.

This design eliminates API-key provisioning and invoicing overhead. Per-call pricing makes large-scale agent operations practical (an autonomous system can make thousands of evaluation calls a day).

The REST API is x402-gated via fastapi-x402; the MCP server uses paymcp in Mode.X402, paying automatically for x402-aware clients and falling back to a guided payment link for clients without a configured wallet. Both settle to the same wallet, and neither has a bypass path — an unpaid call simply receives no verdict.

License

Apache License 2.0 — see LICENSE.