Sub-ms deterministic parsing vs. LLM-based policy for agent safety? Independent developer Midhun Sekhar released MiSeGuard, a deterministic safety layer that proxies Model Context Protocol (MCP) tool calls for autonomous coding agents such as Cursor, Claude Code, Antigravity, OpenCode and Windsurf, scoring each invocation on a 0–100 Blast-Radius Risk Score in sub-millisecond time with no LLM in the loop. MiSeGuard installs via npm (Node.js 18.0 or later) and blocks commands scoring 70–100 with exit code 1, dry-runs commands scoring 30–69 with exit code 2 in strict mode, and allows commands scoring 0–29 with exit code 0, with exit codes guaranteed stable across versions for CI/CD and pre-commit hooks. The project ships a starter config with an allowlist and protected paths including .env*, *.pem, *.key, id_rsa*, ~/.ssh/*, ~/.aws/* and ~/.kube/*, and is not affiliated with any employer of its author. Disclaimer MiSeGuard is an independent personal project created by Midhun Sekhar. It is not affiliated with, endorsed by, or representative of any current, past, or future employer. All development was conducted entirely on personal equipment, during personal time, and without the use of proprietary resources or confidential information. A deterministic safety layer for autonomous coding agents. Runtime circuit breaker and stdio proxy that intercepts MCP tool calls before they reach your OS. AI coding agents can modify your machine. MiSeGuard puts a deterministic security boundary between the agent and your tools. What is MCP? The Model Context Protocol MCP is an open standard that lets autonomous AI agents such as Cursor, Claude Code, Antigravity, OpenCode, Windsurf invoke external tools bash, filesystem, git, terminal over stdio JSON-RPC 2.0. MiSeGuard sits as a transparent, sub-millisecond proxy between your agent and those tool runtimes to inspect, score, and block destructive operations before they reach the real operating system. What Does "Deterministic" Mean? The same command or file mutation with the same configuration always produces the exact identical risk score. No LLM in the loop, no non-deterministic inference, no prompt drift. Global install recommended for CLI use npm install -g miseguard Or run directly via npx npx miseguard --help Or add as a project dev dependency npm install --save-dev miseguard Requirements: Node.js 18.0 or later. miseguard init Choose the method that matches your workflow: - Starting fresh or configuring an agent GUI? Use snippet to generate copy-pasteable JSON: miseguard snippet --tool filesystem --path . - Already have an existing MCP configuration file? Use wrap-config