DCL Trust Oracle

DCL Trust Oracle

DCL Trust Oracle is a deterministic AI audit layer, natively integrated with MCP, that evaluates LLM and agent outputs against configurable policies before and after action. Every verdict is written to a tamper-evident, hash-chained audit log storing only cryptographic metadata — never raw content — enabling privacy-first forensic review.

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DCL Trust Oracle — x402 MCP Server

Python 3.11+ MCP x402 License: MIT dcl-webhook MCP server Smithery Score

Deterministic AI audit layer with cryptographic micropayments via x402 protocol.

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, both metered per call via x402:

  • REST API (webhook_server.py) — direct HTTP integration, x402-gated with fastapi-x402.
  • MCP Server (mcp_server.py) — native Model Context Protocol integration for AI agents, hosted on Smithery, x402-gated with paymcp.

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

pip install -r requirements.txt
python mcp_server.py

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

Tools & Endpoints

Pre-Action Evaluation

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 20 items per transaction. 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

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.

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
}

x402 Integration

All paid endpoints and tools require payment via the x402 protocol before returning a result — no free tier, no bypass. Both the REST API and MCP server settle to the same wallet.

  • Networks: Base, Avalanche, IoTeX
  • Asset: USDC
  • Facilitator (REST): https://x402.org/facilitator (via fastapi-x402)
  • Facilitator (MCP): paymcp in Mode.AUTO — automatic on-chain payment for x402-aware MCP clients, guided payment link (ELICITATION/RESUBMIT) for clients without a wallet. No path skips payment.

Metadata-Only Architecture

DCL Trust Oracle is designed around a hash-based audit trail:

  • Raw content never stored — only SHA-256 hashes and decision metadata
  • Tamper-evident cryptographic chain (SQLite-backed, WAL mode)
  • Chain survives server restarts — audit records persist indefinitely
  • Verifiable integrity via GET /chain/status
  • Full export via GET /chain/export
  • Shared chain across REST and MCP — a tx_hash returned by one interface can be audited through the other

Each audit record contains: tx_hash, prev_hash, verdict, input_hash, policy_hash, agent_id, reason, confidence, task_type, timestamp, and drift_context.

Built-in Policies

Policy Min Confidence Purpose
default 0.70 General-purpose evaluation
anti_jailbreak 0.80 Detects prompt injection, role-hijacking, DAN-style attacks
safety 0.75 Baseline harmful-pattern screening
content_quality 0.85 Quality assurance, format adherence, drift detection

Custom policies can be passed inline as YAML via the policy field.

Links

  • Live API: https://fronesislabs.com/docs
  • MCP Server: https://mcp.fronesislabs.com
  • MCP Manifest: https://fronesislabs.com/.well-known/agent.json
  • GitHub: https://github.com/Fronesis-Labs/dcl-webhook
  • Smithery.ai: https://smithery.ai/servers/fronesislabs/dcl-trust-oracle
  • Glama.ai: https://glama.ai/mcp/servers/Fronesis-Labs/dcl-webhook

Contact

partnership@fronesislabs.com

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