A unified MCP server providing observability, safety control, and behavior evolution for high-agency AI agents through tracing, replaying, and auditing. It features real-time firewall guardrails and ML-driven anomaly detection to monitor, block, or fork agent actions based on risk.
MCP server that provides AI agents with persistent memory, cross-agent sharing, and context management, enabling them to remember conversations, track complex tasks, and evolve skills across tools.
A local-first MCP server that gives AI coding agents runtime visibility and AI-managed debug logging. It replaces blind print() debugging by turning runtime execution into causal chains, allowing agents to instantly locate bugs by finding missing .success events in Python and TypeScript code. Single binary with MCP, CLI, and HTTP interfaces.