Flagged: sudo usage. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by Bredrumb · MCP Server · ★ 52
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is TomoriBot safe to install? View the security audit →
TomoriBot A self-hosted and customizable personal AI assistant/role-playing system for Discord with memory, multiple personas, tool calling, multimodality, and API/local model support. English | 日本語 Latest Releases · Invite TomoriBot · Discord Server · Report Bug · Request Feature [![License
| Stars | 52 |
| Forks | 11 |
| Language | TypeScript |
| Category | MCP Server |
| License | AGPL-3.0 |
| Quality Score | 69.6038002182561/100 |
| Open Issues | 7 |
| Last Updated | 2026-09-20 |
| Created | 2023-07-06 |
| Platforms | mcp, node |
| Est. Tokens | ~20k |
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TomoriBot is A highly customizable personal AI assistant for Discord featuring smart agentic AI features such as memory, personas, tool usage, and more! | 長期記憶やペルソナ、ツール連携を完備。 次世代の「自律型AIエージェント」Discordボット!. It is categorized as a MCP Server with 52 GitHub stars.
TomoriBot is primarily written in TypeScript. It covers topics such as agentic-ai, ai-agent, ai-assistant.
You can find installation instructions and usage details in the TomoriBot GitHub repository at github.com/Bredrumb/TomoriBot. The project has 52 stars and 11 forks, indicating an active community.
TomoriBot is released under the AGPL-3.0 license, making it free to use and modify according to the license terms.
The top alternatives to TomoriBot on Agent Skills Hub include c4-genai-suite, lucid-memory, cognithor. 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: