better-chatbot: Formerly Better Chatbot. Navigator is an open-source AI workspace for agents, MCP and workflow automation

by keinsaasforever · MCP Server · ★ 1.2k

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

Security audit verdict: SAFE · quality 68/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. 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.

agentaiai-chatbotautomationchatbotclaudegeminilow-codemcpmcp-client

Quick Facts

Stars1,196
Forks349
LanguageTypeScript
CategoryMCP Server
LicenseMIT
Quality Score68/100
Open Issues57
Last Updated2026-11-06
Created2025-04-13
Platformsbrowser, claude-code, gemini, mcp, node
Est. Tokens~18k

About better-chatbot

Keinsaas Navigator - A better open-source AI chatbot for individuals and teams. Originally created by Choi Sung Keun....

Compatible Skills

These tools work well together with better-chatbot for enhanced workflows:

  • openclaw-nerve — semantic(0.18)+complementary+rare_topics+same_lang+similar_pop+shared_platform (61%)
  • ai-agent-automation — semantic(0.24)+complementary+same_lang+similar_pop+shared_platform (58%)
  • giselle — semantic(0.19)+complementary+rare_topics+same_lang+similar_pop+shared_platform (56%)
  • openai-agents-js — semantic(0.17)+complementary+same_lang+similar_pop+shared_platform (56%)

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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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