ai-platform-engineering — security grade SAFE, quality 58/100

Security audit verdict: SAFE · quality 58/100

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 caipe-io · MCP Server · ★ 419

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

🔒 Is ai-platform-engineering safe to install? View the security audit →

About ai-platform-engineering

🤖 CAIPE: An Opensource Platform for AI Platform Engineering 🚀 Getting Started 🗺️ Roadmap What is CAIPE? CAIPE (pronounced like cape 🦸) is an open-source AI platform for building, deploying, governing, and operating AI agents and agentic workflows for platform engineering and beyond. It combines agent creation, runtime execution, workflow automation, skills and MCP integrations, enterprise knowledge, identity and authorization, observability, and multi-channel experiences. 🗓️ Weekly Meetings Every Monday 🕕 19:00–20:00 CET 🕘 10:00–11:00 PST 🔗 Webex Meeting 📥 .ics Download 💬 Slack Not in CNCF Slack? Join here first [Join the CAIPE community channel](https://cloud-native.slack.com/archives/

agent-orchestrationagentic-aiagentic-workflowsagentsaiai-agentsai-governanceai-platformartificial-intelligencecaipe

Quick Facts

Stars419
Forks85
LanguageTypeScript
CategoryMCP Server
LicenseApache-2.0
Quality Score57.7944006022241/100
Open Issues397
Last Updated2026-09-22
Created2025-06-12
Platformsk8s, mcp, node
Est. Tokens~14k

Compatible Skills

These tools work well together with ai-platform-engineering for enhanced workflows:

  • kite — semantic(0.19)+complementary+rare_topics+same_lang+similar_pop+shared_platform (61%)
  • cortex — semantic(0.28)+complementary+same_lang+similar_pop+shared_platform (60%)
  • markus — semantic(0.25)+complementary+same_lang+similar_pop+shared_platform (59%)
  • overlay-web — semantic(0.24)+complementary+same_lang+similar_pop+shared_platform (58%)
  • cli — semantic(0.24)+complementary+same_lang+similar_pop+shared_platform (58%)

ai-platform-engineering alternative? Top 6 similar tools

Looking for a ai-platform-engineering alternative? If you're comparing ai-platform-engineering 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.

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  • superglue by superglue-ai · ⭐ 2.0k

    superglue (YC W25) builds integrations and tools from natural language. Get production-grade tools for long ta

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Frequently Asked Questions

What is ai-platform-engineering?

ai-platform-engineering is CAIPE is an open-source AI platform for building, governing, and operating AI agents and agentic workflows for platform engineering and beyond.. It is categorized as a MCP Server with 419 GitHub stars.

What programming language is ai-platform-engineering written in?

ai-platform-engineering is primarily written in TypeScript. It covers topics such as agent-orchestration, agentic-ai, agentic-workflows.

How do I install or use ai-platform-engineering?

You can find installation instructions and usage details in the ai-platform-engineering GitHub repository at github.com/caipe-io/ai-platform-engineering. The project has 419 stars and 85 forks, indicating an active community.

What license does ai-platform-engineering use?

ai-platform-engineering is released under the Apache-2.0 license, making it free to use and modify according to the license terms.

What are the best alternatives to ai-platform-engineering?

The top alternatives to ai-platform-engineering on Agent Skills Hub include sre, oreilly-ai-agents, AgenticGoKit. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

How this security grade is produced

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:

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