mimo2codex: 让最新版 OpenAI Codex CLI / Codex 桌面端接入主流大模型的本地代理。内置 小米 MiMo V2.5/DeepSeek V4 Pro

by 7as0nch · Codex Skill · ★ 626

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

How to install mimo2codex

npm install -g mimo2codex     # 1. install (Node ≥ 18)

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

Security audit verdict: SAFE · quality 63/100

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.

codexdeepseekmacosmimomimo2codexminimaxnpmwindows

Quick Facts

Stars626
Forks64
LanguageTypeScript
CategoryCodex Skill
LicenseMIT
Quality Score63/100
Open Issues21
Last Updated2026-07-04
Created2026-05-07
Platformscli, codex, node
Est. Tokens~15k

About mimo2codex

mimo2codex English · 简体中文 · Docs site Local proxy that lets the latest OpenAI Codex CLI / desktop talk to virtually any modern LLM. Built-in support for Xiaomi MiMo V2.5 and DeepSeek V4 Pro, plus a generic provider mechanism for any OpenAI Chat Completions-compatible (Qwen / GLM / Kimi / vLLM / Ollama / LM Stu

Compatible Skills

These tools work well together with mimo2codex for enhanced workflows:

  • ovo-local-llm — semantic(0.17)+complementary+shared_fw(ollama,openai)+same_lang+similar_pop+shared_platform (67%)
  • open-responses-server — semantic(0.44)+complementary+shared_fw(ollama,openai)+similar_pop+shared_platform (66%)
  • codex-mcp-server — semantic(0.18)+complementary+shared_fw(openai)+same_lang+similar_pop+shared_platform (64%)
  • houtini-lm — semantic(0.23)+complementary+shared_fw(ollama,openai)+similar_pop+shared_platform (64%)
  • openai-assistant-swarm — semantic(0.18)+complementary+shared_fw(openai)+rare_topics+same_lang+similar_pop+shared_platform (64%)

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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:

View on GitHub → Browse Codex Skill tools