The approval and accountability layer for agentic AI. Identity → Policy → Approval → Trace. Try: npx sidclaw-mcp-guard demo

System of record for AI tool risk: inventory, policy enforcement, approvals, and audit-ready evidence.

ForceField Python SDK -- AI security in 3 lines of code. Prompt injection detection, PII redaction, security evals, tool governance. GitHub Action, pre-commit hook, Homebrew, VS Code extension.

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Paid remote MCP for schema drift checks, tool-schema approvals, compatibility receipts, breaking-change explanations, and release audit logs.

Deterministic pre-execution gate for one credentialed tool request: explicit policy, allow/deny decision, and inspectable decision artifact.

Python FastAPI service for evaluating MCP server and tool policies, trust posture, destructive-action controls, and operator-facing review workflows.

Harness engine for AI Agents. From demo to production.

Deterministic security architecture model for AI agent systems with deterministic permission and tool control.

Deterministic security control layer for agent tool calls.