acodex: Local MCP automation bridge for the Codex desktop app, with CLI, HTTP server, and live codex_app. tool access

by maksimzayats · MCP Server · ★ 59

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

Featured in: OpenAI Codex Skills

How to install acodex

uv add acodex
uv add "acodex[structured-output]"

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 70/100

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.

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.

agentaiautomationclicodexcodex-clicodex-pythoncodex-sdkopenai-codexpython

Quick Facts

Stars59
Forks1
LanguagePython
CategoryMCP Server
LicenseMIT
Quality Score70/100
Last Updated2026-11-06
Created2026-02-14
Platformscli, codex, mcp, python
Est. Tokens~14k

About acodex

acodex acodex is a fast, typed Python SDK for Codex CLI workflows (sync/async, streaming, structured output, images, safety controls), and API parity with the TypeScript SDK. What is acodex? acodex spawns the CLI and exchanges JSONL events over stdin/stdout so you can run agent threads from Python with a fully typed surface: sync + async clients, streaming events, structured output, image inputs,...

acodex alternative? Top 6 similar tools

Looking for a acodex alternative? If you're comparing acodex with other mcp server tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.

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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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