Fronesis-Labs/dcl-webhook

**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
Server runs on http://localhost:8080
MCP Server
**Production (hosted):**
Streamable HTTP transport — point any MCP client here directly, no setup required.
**Local development:**
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 |
| --- | --- | --- | --- |