by decionis · MCP Server · ★ 671
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
git clone https://github.com/decionis/agent-safe-pipeline.gitTaken from the project's README on GitHub. Check the security audit before running it.
None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.
| Stars | 671 |
| Forks | 57 |
| Language | TypeScript |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 70/100 |
| Open Issues | 19 |
| Last Updated | 2026-11-03 |
| Created | 2026-08-13 |
| Platforms | aws, docker, k8s, mcp, node |
| Est. Tokens | ~15k |
Agent-Safe Pipeline Let agents propose. Let policy decide. Agent-Safe Pipeline is a reference architecture for executing AI-agent actions through an independent authorization boundary. This repository is a library and runnable reference implementation, not a hosted authorization service or a substitute for provider-side identity, least privilege, network isolation, and incident response.
These tools work well together with agent-safe-pipeline for enhanced workflows:
Looking for a agent-safe-pipeline alternative? If you're comparing agent-safe-pipeline with other mcp server tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
Open-source, self-hosted AI agent platform for your company's AI teammates. Build, run and govern agents on yo
Agent orchestration & security template featuring MCP tool building, agent2agent workflows, mechanistic interp
Agent-ready DevOps, security, infrastructure, and compliance knowledge base with 80+ skills across Kubernetes,
Python and TypeScript SDKs for verifiable evidence of AI agent actions. Signed receipts, policy enforcement, a
Runtime policy enforcement for AI agents. Cryptographic audit trail, human-in-the-loop approvals, kill switch.
Run coding agents without babysitting them. Keep jobs focused, bounded, checked and accountable from start to
Explore other popular mcp server tools:
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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: