Universal governance layer for AI agents — MCP-native,
fail-closed, LNN interpretability. Governed receipts, IPFS audit proofs, and
rollback for any agent in any framework.
Server-enforced workflow discipline for AI agents. An MCP server providing persistent work items, dependency graphs, quality gates, and actor attribution. Schemas define what agents must produce — the server blocks the call if they don't. Works with any MCP-compatible client.
MCP server that enforces governance on agentic decisions with auditable evidence records, providing tools for understanding, calibrating confidence, and navigating handoffs based on policy.
Local-first MCP Work Model for coding agents: retrieves scored memory, records commitments, and credits outcomes from tests, reviews, replies, or owner approval. Public repo includes Apache-2.0 integration glue; the local engine binary is proprietary.
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.