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 sirkirby · MCP Server · ★ 844
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is unifi-mcp safe to install? View the security audit →
UniFi MCP Leverage agents and agentic AI workflows to manage your UniFi deployment. Servers What is this? UniFi MCP is a collection of Model Context Protocol servers that let AI assistants and automation tools interact with Ubiquiti UniFi controllers. Each server targets a specific UniFi application (Network, Protect, Access) and exposes its functionality as MCP tools — queryable, composable, and safe
| Stars | 844 |
| Forks | 113 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 75.7484036839543/100 |
| Open Issues | 19 |
| Last Updated | 2026-09-21 |
| Created | 2025-04-21 |
| Platforms | mcp, python |
| Est. Tokens | ~14k |
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unifi-mcp is MCP servers & Graph API for the UniFi suite of applications, Network, Protect, and Access. It is categorized as a MCP Server with 844 GitHub stars.
unifi-mcp is primarily written in Python. It covers topics such as agentic-ai, home-automation, mcp-server.
You can find installation instructions and usage details in the unifi-mcp GitHub repository at github.com/sirkirby/unifi-mcp. The project has 844 stars and 113 forks, indicating an active community.
unifi-mcp is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to unifi-mcp on Agent Skills Hub include paperbanana, mcp-memory-service, paperdebugger. 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: