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 Lykhoyda · MCP Server · ★ 18
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is ask-llm safe to install? View the security audit →
MCP server for AI-to-AI collaboration — bridge Claude with Gemini, Codex, and other LLMs for code review, second opinions, and plan debate
| Stars | 18 |
| Forks | 5 |
| Language | TypeScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 69.4061388550615/100 |
| Open Issues | 10 |
| Last Updated | 2026-10-02 |
| Created | 2026-02-19 |
| Platforms | claude-code, codex, gemini, mcp, node |
| Est. Tokens | ~16k |
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ask-llm is MCP server for AI-to-AI collaboration — bridge Claude with Gemini, Codex, and other LLMs for code review, second opinions, and plan debate. It is categorized as a MCP Server with 18 GitHub stars.
ask-llm is primarily written in TypeScript. It covers topics such as ai, claude, claude-ai.
You can find installation instructions and usage details in the ask-llm GitHub repository at github.com/Lykhoyda/ask-llm. The project has 18 stars and 5 forks, indicating an active community.
ask-llm is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to ask-llm on Agent Skills Hub include claude-prompt-engineering-guide, claude-emporium, forgecat-agent-profiles. 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: