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 ThreeMoonsLab · MCP Server · ★ 89
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is agents-shipgate safe to install? View the security audit →
Agents Shipgate Your coding agent changed what your AI agent can do — Agents Shipgate shows you what changed before it merges. The deterministic merge gate for AI-generated agent capability changes. Local-first and static by default — no agent execution, tool calls, LLM calls, or network access. Agents Shipgate is an open-source CLI and GitHub Action for local-first, static Tool-Use Readiness review. It scans MCP, OpenAPI, OpenAI Agents SDK, Anthropic Messages API, Google ADK, LangChain/LangGraph, CrewAI,
| Stars | 89 |
| Forks | 3 |
| Language | Python |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 67.7961373807449/100 |
| Open Issues | 113 |
| Last Updated | 2026-09-23 |
| Created | 2026-04-25 |
| Platforms | cli, mcp, python |
| Est. Tokens | ~20k |
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agents-shipgate is The deterministic merge gate for AI-generated agent capability changes — a local-first, static Tool-Use Readiness review for MCP, OpenAPI, and SDK tool surfaces. Open-source CLI + GitHub Action.. It is categorized as a MCP Server with 89 GitHub stars.
agents-shipgate is primarily written in Python. It covers topics such as agent-governance, agent-release-readiness, ai-agent-security.
You can find installation instructions and usage details in the agents-shipgate GitHub repository at github.com/ThreeMoonsLab/agents-shipgate. The project has 89 stars and 3 forks, indicating an active community.
agents-shipgate is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to agents-shipgate on Agent Skills Hub include faramesh-core, DashClaw, oreilly-ai-agents. 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: