No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by elliot35 · MCP Server · ★ 88
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is deterministic-agent-control-protocol safe to install? View the security audit →
Self-Evolving Deterministic Agent Control Protocol A governance gateway for AI agents — making every action bounded, auditable, reversible, and explainable. Works transparently with Cursor, Claude Code, Codex, and any MCP-compatible agent. Also supports shell command governance and a language-agnostic HTTP API. 🛡️ Governance in Action <img src="assets/mcp-config.gif" alt="Setting up governa
| Stars | 88 |
| Forks | 7 |
| Language | TypeScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 73.457535870405/100 |
| Last Updated | 2026-02-12 |
| Created | 2026-02-07 |
| Platforms | claude-code, codex, mcp, node |
| Est. Tokens | ~3846k |
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deterministic-agent-control-protocol is Governance gateway for AI agents — bounded, auditable, session-aware control with MCP proxy, shell proxy & HTTP API. Works with Cursor, Claude Code, Codex, and any MCP-compatible agent.. It is categorized as a MCP Server with 88 GitHub stars.
deterministic-agent-control-protocol is primarily written in TypeScript. It covers topics such as agent-control, agent-governance, ai-agent.
You can find installation instructions and usage details in the deterministic-agent-control-protocol GitHub repository at github.com/elliot35/deterministic-agent-control-protocol. The project has 88 stars and 7 forks, indicating an active community.
deterministic-agent-control-protocol is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to deterministic-agent-control-protocol on Agent Skills Hub include mcp-fusion, claude-historian-mcp, claude-prompts. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: