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 limelit-co · MCP Server · ★ 153
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is open safe to install? View the security audit →
Limelit Open Self-hosted AI visibility tracking. One binary, your keys, your data. Track how ChatGPT, Claude, Perplexity, Gemini, Google AI Overview and Google AI Mode mention and cite your brand against your competitors. Live: <a href="ht
| Stars | 153 |
| Forks | 140 |
| Language | Go |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 62.9166634460626/100 |
| Open Issues | 6 |
| Last Updated | 2026-10-01 |
| Created | 2026-09-11 |
| Platforms | claude-code, gemini, go, mcp |
| Est. Tokens | ~23k |
These tools work well together with open for enhanced workflows:
Looking for a open alternative? If you're comparing open 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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Explore other popular mcp server tools:
open is Self-hosted AI visibility tracking (AEO / GEO / LLMO). Track how ChatGPT, Claude, Perplexity, Gemini and Google AI Overviews mention and cite your brand. One Go binary, SQLite, MCP-first, bring your o. It is categorized as a MCP Server with 153 GitHub stars.
open is primarily written in Go. It covers topics such as aeo, ai-search-optimization, ai-seo.
You can find installation instructions and usage details in the open GitHub repository at github.com/limelit-co/open. The project has 153 stars and 140 forks, indicating an active community.
open is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to open on Agent Skills Hub include eGEOagents, canonry, ansvisor. 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: