arifOS vs ADR
arifOS: arifOS is the world's first production-grade Constitutional AI Governance System, enforcing ethical, logical, and safety constraints on AI outputs through 13 physics-grounded constitutional floors. Unlike traditional safety frameworks, it treats AI governance as thermodynamic work, validating outputs pre-execution via a 5-organ pipeline and offering auditable decisions.; ADR: ADR (Agentic Detection and Response) is an open-source framework designed to secure AI agents utilizing the Model Context Protocol (MCP). It comprises an ADR Sensor for telemetry collection and an ADR Detector, which serves as a dual-agent benchmark and detection system.
TL;DR
Ensuring ethical, logical, and safety compliance of AI outputs in production environments.
- You research detection for MCP-based agents and want to reproduce the MLSys 2026 ADR paper.
- You want a benchmark: ADR-Bench has 133 MCP servers and 303 tasks with baselines.
- You want to collect telemetry from Claude Code, Cursor and Codex into one schema with the sensor.
- You want a packaged product to deploy: this is research code for a paper.
- You want the ADR Explorer red-teaming engine: the README says it is not included.
- You cannot pay for Anthropic and OpenAI API calls: the default detector needs both.
Side-by-Side Comparison
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