Open intelligence router for LLM agents
Deterministic safety solutions for probabilistic AI agents
MCP middleware that blocks dangerous AI agent actions using a simple YAML config
Merge gates and safety checks for AI coding agents. Works with Claude Code, Cursor, Windsurf, Codex via MCP. Detect scope violations, missing tests, and risks before merge.
Secure every action your AI agents take (Claude Code, Codex, MCP). Blocks secret access, gates risky commands, and enforces allow/deny/approval before actions run.
Deterministic tool-call guardrails for pi — enforce rules with before-tool hooks instead of prompts
Runtime guardrails for AI agents that enforce token budgets, loop limits, and tool rate limits locally.
Portable runtime policy and audit layer for AI agents - HTTP/HTTPS proxy enforcing egress policies, inspecting content, materializing secrets, and recording every decision.
Semantic mistake-memory and guardrail for AI agents. Stops agents from repeating the same failures using causal graphs and semantic matching. Supports MCP, LangGraph, and in-process Python.
Deterministic governance engine for AI agents. Enforce rules defined in .md governance files across AI systems.
Teams and Solo Devs Claude Code hooks setup for observability and guardrails. Understand how skill, subagents, prompts are working and where is claude struggling to improve systematically
On-chain guardrails for AI agents — EIP-7702 spend limits, cryptographic execution receipts, automated dispute resolution. No agent should hold unguarded keys.
Who watches the agents?
Discipline hooks for Claude Code. Stops the agent from claiming 'done' without proof, blocks accidental writes to ~/.claude config, and routes prompts to skills via local pgvector with zero Anthropic tokens.
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