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.

REST Endpoint	MCP Tool	Price	Description
POST /evaluate/fast	dcl_evaluate_fast	$0.01	Fast policy check for low-risk outputs. Returns tamper-evident tx_hash.
POST /evaluate/strict	dcl_evaluate_strict	$0.05	Deep analysis for high-stakes outputs with higher confidence thresholds.
POST /evaluate/jailbreak	dcl_evaluate_jailbreak	$0.02	Instruction adherence check — detects prompt injection patterns and role-hijacking attempts.
POST /evaluate/safety	dcl_evaluate_safety	$0.01	Baseline screening for known harmful text patterns. Optimized for high throughput.
POST /evaluate/quality	dcl_evaluate_quality	$0.03	Content quality & drift check — evaluates format adherence and contextual drift.
POST /evaluate/batch	dcl_evaluate_batch	$0.10	Bulk processing — up to 200 items per MCP call (REST default max_items: 20). Cost-effective for multi-turn history.

Session Management

REST Endpoint	MCP Tool	Price	Description
POST /pipeline/start	dcl_pipeline_start	$0.05	Initializes a long-running audit session for continuous drift tracking. Returns pipeline_id.

Post-Action Forensics

When something did go wrong, reconstruct exactly what happened.

REST Endpoint	MCP Tool	Price	Description
GET /audit/{tx_hash}	dcl_audit_decode	$0.10	Basic post-action audit — returns verdict, confidence, agent_id, reason by tx_hash.
GET /audit/{tx_hash}/deep	dcl_audit_decode_deep	$0.50	Deep forensic audit — includes drift context, tamper-evidence indices, environmental metadata.

Post-Action Scans

REST Endpoint	MCP Tool	Price	Description
POST /evaluate/secrets	dcl_evaluate_secrets	$0.02	Secret & credential leak scan.
POST /evaluate/pii	dcl_evaluate_pii	$0.02	PII detection scan.

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.

REST Endpoint	Price	Description
POST /sentinel/register	$49.00 / 30d	Register a skill/repo for continuous monitoring. Requires passing initial baseline audit (score >= 0.80; returns HTTP 422 if failed). Issues webhook_secret.
POST /sentinel/webhook/{webhook_secret}	Free	GitHub Webhook receiver. Audits new release tags, blocks regressions, and logs tamper-evident events.
POST /sentinel/scan	$0.05–$0.50	Pay-per-call repository audit (update_rescan, deep_scan, forensic_audit).
GET /sentinel/status/{repo_full_name}	Free	Query skill security status (active, blocked, unregistered) and last known good version.
POST /sentinel/renew	$49.00 / 30d	Extend 30-day monitoring entitlement for a registered skill (owner-verified).
GET /sentinel/prices	Free	Returns current price breakdown for Sentinel services.

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).

MCP Tool	Price	Description
dcl_evaluate_jailbreak_crypto	$0.02	Crypto-specific jailbreak & injection detection.
dcl_evaluate_wallet	$0.02	Wallet secret guardian.
dcl_evaluate_trade	$0.02	Trade decision verifier.
dcl_evaluate_mev	$0.03	MEV & market-abuse compliance screen.
dcl_evaluate_signal	$0.03	Market signal fabrication screen.
dcl_evaluate_output_sanitizer	$0.02	Output sanitizer — final gate.
dcl_commit	$0.01	Leibniz Layer crypto commit — seal a decision to the audit chain.

Utility (free, REST only)

Endpoint	Description
GET /health	Service status and chain length
GET /policies	List of built-in policy names
GET /chain/status	Chain integrity, drift mode, drift score
GET /chain/export	Full chain export with integrity verification

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.