TomoriBot: A highly customizable personal AI assistant for Discord featuring smart agentic AI features such as memory

by Bredrumb · MCP Server · ★ 63

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install TomoriBot

git clone https://github.com/Bredrumb/TomoriBot.git

Taken from the project's README on GitHub. Check the security audit before running it.

Security audit verdict: CAUTION · quality 70/100

Flagged: sudo usage. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

agentic-aiai-agentai-assistantdiscord-botllmmcpmemoryopenaipersonarag

Quick Facts

Stars63
Forks16
LanguageTypeScript
CategoryMCP Server
LicenseAGPL-3.0
Quality Score70/100
Open Issues4
Last Updated2026-11-03
Created2023-07-06
Platformsmcp, node
Est. Tokens~20k

About TomoriBot

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

Compatible Skills

These tools work well together with TomoriBot for enhanced workflows:

  • home-mind — semantic(0.19)+complementary+same_lang+similar_pop+shared_platform (52%)
  • mcp-discord — semantic(0.18)+complementary+same_lang+similar_pop+shared_platform (51%)
  • mcp-think-tank — semantic(0.16)+complementary+same_lang+similar_pop+shared_platform (51%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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:

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