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 heshengtao · MCP Server · ★ 2.3k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is comfyui_LLM_party safe to install? View the security audit →
bilibili · youtube · text tutorial · Cloud disk address · QQ group · discord · About us C omfyuillmp
| Stars | 2,334 |
| Forks | 198 |
| Language | Python |
| Category | MCP Server |
| License | AGPL-3.0 |
| Quality Score | 60.8953435602967/100 |
| Open Issues | 80 |
| Last Updated | 2026-07-29 |
| Created | 2024-04-13 |
| Platforms | gemini, mcp, python |
| Est. Tokens | ~18k |
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comfyui_LLM_party is LLM Agent Framework in ComfyUI includes MCP sever, Omost,GPT-sovits, ChatTTS,GOT-OCR2.0, and FLUX prompt nodes,access to Feishu,discord,and adapts to all llms with similar openai / aisuite interfaces,. It is categorized as a MCP Server with 2.3k GitHub stars.
comfyui_LLM_party is primarily written in Python. It covers topics such as agent, comfyui, dify.
You can find installation instructions and usage details in the comfyui_LLM_party GitHub repository at github.com/heshengtao/comfyui_LLM_party. The project has 2.3k stars and 198 forks, indicating an active community.
comfyui_LLM_party is released under the AGPL-3.0 license, making it free to use and modify according to the license terms.
The top alternatives to comfyui_LLM_party on Agent Skills Hub include ComfyUI-IF_AI_tools, better-chatbot, flock. 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: