Side-by-side comparison of two Model Context Protocol servers — install paths, tools, quality signals, and directory engagement so you can pick the right one for Claude, Cursor, and other MCP clients.
Proof-of-behavior enforcement for AI agents. Define behavioral covenant rules (permit/forbid/require), enforce at runtime before execution, get SHA-256 hash-chained tamper-evident audit logs, and verify compliance independently. Cross-agent verification handshake — no proof, no transaction. MIT licensed, 4,244 tests.
Share encrypted, self-destructing secrets from your AI agent. Zero-knowledge E2E encryption. Agent-blind input sources (env:, file:, dotenv:) keep secrets out of LLM context.