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 srbhptl39 · MCP Server · ★ 2.6k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is MCP-SuperAssistant safe to install? View the security audit →
-- MCP SuperAssistant Chrome Extension Brings MCP to ChatGPT, Perplexity, Grok, Gemini, Google AI Studio, OpenRouter, Kimi, Github Copilot, Mistral and more... 🌐 Visit Official Website Installation <a h
| Stars | 2,585 |
| Forks | 362 |
| Language | TypeScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 74.6404260170884/100 |
| Open Issues | 100 |
| Last Updated | 2026-02-09 |
| Created | 2025-04-26 |
| Platforms | gemini, mcp, node |
| Est. Tokens | ~250k |
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MCP-SuperAssistant is Brings MCP to ChatGPT, DeepSeek, Perplexity, Grok, Gemini, Google AI Studio, OpenRouter, DeepSeek, T3 Chat and more.... It is categorized as a MCP Server with 2.6k GitHub stars.
MCP-SuperAssistant is primarily written in TypeScript. It covers topics such as aistudio, assistant, chatgpt.
You can find installation instructions and usage details in the MCP-SuperAssistant GitHub repository at github.com/srbhptl39/MCP-SuperAssistant. The project has 2.6k stars and 362 forks, indicating an active community.
MCP-SuperAssistant is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to MCP-SuperAssistant on Agent Skills Hub include papersgpt-for-zotero, py-gpt, UnrealGenAISupport. 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: