Policy-based governance for AI agent tool calls. YAML policies, approval gates, risk assessment, and audit logging across LangChain, OpenAI, Anthropic, and MCP.
Governance runtime for AI agents: a guard tool evaluates risky actions against policy before they execute (block / warn / require human approval), approvals route to a human queue, and every action becomes a replayable decision record with per-action spend tracking. Runs over stdio via npx @dashclaw/mcp-server; works with Claude Code, Codex, LangChain, CrewAI, or any MCP host.