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by kamesh231 • Uncategorized
An MCP server providing human-agent collaboration primitives with action attribution and trust management.
Propose actions and receive trust-based approval before execution.
That require transparent action attribution and audit logging for governance.
Escalate tasks to humans with structured context and handle overrides.
This MCP server adds collaboration primitives to AI agents, enabling intent declaration, trust scoring, human handoffs, action attribution, and override handling. It includes a high-performance security proxy called cowork-sentry that enforces action attribution with immutable audit logs, tamper-evident hash chains, and PII sanitization. The system improves AI governance by making agent actions transparent, accountable, and auditable, while allowing trust to be earned or degraded based on overrides.
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