DingDawg Loop Protocol (DDLP) — safe scheduled AI agents
with
governance gates. Every loop execution is verified, receipted, and
fail-closed. MCP-native, works with CrewAI, LangGraph, Claude Code, Cursor.
Fail-closed AI agent governance — approve or block agent actions
in real time, score compliance risk, and generate tamper-evident receipts.
Free tier: 10 governed actions/day. Upgrade for unlimited + Ed25519-signed
audit receipts.
Governance kernel for AI agents — policy enforcement, code safety verification,
multi-model hallucination detection (CMVK), trust attestation (IATP), and immutable
audit trails. Works with Claude Desktop, Cursor, and any MCP client.
A governance proxy for AI tools — every MCP/agent tool call is policy-gated, secret-redacted, and written to a hash-chained, offline-verifiable audit trail.
Provides cryptographic governance receipts for AI agents, enabling pre-execution evaluation and signed verdicts (EXECUTE/BLOCK/REVIEW/SHADOW) with offline-verifiable audit trails.
AI agent governance through MCP - policy enforcement, quantum-safe audit trails (ML-DSA), multi-party authorization, and compliance reporting for AI agents.
Cryptographic accountability for AI agents. Ed25519-signed receipts for every MCP tool call. Constraints, chains, AI judgment, invoicing, and local dashboard included.