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 s-nagaev · MCP Server · ★ 56
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is chibi safe to install? View the security audit →
Your Digital Companion. Not a Tool. A Partner. Self-hosted, asynchronous Telegram bot that orchestrates multiple AI providers, tools, and sub-agents to get real work done. <img src="https://img.shields.io/badge/docs-chibi.bot-blue" alt="Doc
| Stars | 56 |
| Forks | 12 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 66.7726960871211/100 |
| Open Issues | 3 |
| Last Updated | 2026-09-23 |
| Created | 2023-03-23 |
| Platforms | claude-code, docker, gemini, mcp, python |
| Est. Tokens | ~16k |
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chibi is Your Digital Companion. Self-hosted Telegram bot orchestrating multiple AI providers (OpenAI, Anthropic, Google, xAI, DeepSeek, Mistral, Alibaba, MiniMax) with autonomous agent capabilities, MCP integ. It is categorized as a MCP Server with 56 GitHub stars.
chibi is primarily written in Python. It covers topics such as ai-agent, anthropic, autonomous-agents.
You can find installation instructions and usage details in the chibi GitHub repository at github.com/s-nagaev/chibi. The project has 56 stars and 12 forks, indicating an active community.
chibi is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to chibi on Agent Skills Hub include c4-genai-suite, captain-claw, Cerno-Agentic-Local-Deep-Research. 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: