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 decionis · MCP Server · ★ 533
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is agent-safe-pipeline safe to install? View the security audit →
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. Its safety claims apply only when the documented trust boundary is preserved. text Agent - immutable intent - Decionis - ALLOW / ESCALATE / BLOCK - SafeExecutor - API |
| Stars | 533 |
| Forks | 57 |
| Language | TypeScript |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 69.594319382287/100 |
| Open Issues | 18 |
| Last Updated | 2026-09-16 |
| Created | 2026-08-13 |
| Platforms | mcp, node |
| Est. Tokens | ~15k |
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agent-safe-pipeline is Reference architecture for AI agents that propose actions but cannot authorize them — immutable intent capture, an independent Decionis policy verdict (ALLOW/ESCALATE/BLOCK), verified human approval, . It is categorized as a MCP Server with 533 GitHub stars.
agent-safe-pipeline is primarily written in TypeScript. It covers topics such as agentic-ai, ai-agent-permissions, ai-agents.
You can find installation instructions and usage details in the agent-safe-pipeline GitHub repository at github.com/decionis/agent-safe-pipeline. The project has 533 stars and 57 forks, indicating an active community.
agent-safe-pipeline is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to agent-safe-pipeline on Agent Skills Hub include template-repo, mcp-memory-service, 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: