io.github.xiaolai/codex-octopus

Official registry AI and agents

Spawn multiple specialized Codex agents as MCP servers, each independently configured.

Install

Add this to your client's MCP configuration (Claude Desktop: claude_desktop_config.json; Cursor: .cursor/mcp.json; VS Code and others use the same "mcpServers" shape).

NPM package codex-octopus
Claude Code
claude mcp add codex-octopus -e 'CODEX_API_KEY=<your codex_api_key>' -e 'CODEX_TOOL_NAME=<CODEX_TOOL_NAME>' -e 'CODEX_MODEL=<CODEX_MODEL>' -e 'CODEX_SANDBOX_MODE=<CODEX_SANDBOX_MODE>' -e 'CODEX_APPROVAL_POLICY=<CODEX_APPROVAL_POLICY>' -e 'CODEX_APPEND_INSTRUCTIONS=<CODEX_APPEND_INSTRUCTIONS>' -e 'CODEX_FACTORY_ONLY=<CODEX_FACTORY_ONLY>' -- npx -y codex-octopus@1.0.1
JSON configuration (Claude Desktop, Cursor, VS Code)
{
    "mcpServers": {
        "codex-octopus": {
            "command": "npx",
            "args": [
                "-y",
                "codex-octopus@1.0.1"
            ],
            "env": {
                "CODEX_API_KEY": "<your codex_api_key>",
                "CODEX_TOOL_NAME": "<CODEX_TOOL_NAME>",
                "CODEX_MODEL": "<CODEX_MODEL>",
                "CODEX_SANDBOX_MODE": "<CODEX_SANDBOX_MODE>",
                "CODEX_APPROVAL_POLICY": "<CODEX_APPROVAL_POLICY>",
                "CODEX_APPEND_INSTRUCTIONS": "<CODEX_APPEND_INSTRUCTIONS>",
                "CODEX_FACTORY_ONLY": "<CODEX_FACTORY_ONLY>"
            }
        }
    }
}

Environment variables

  • CODEX_API_KEY secret OpenAI API key (leave unset to inherit from parent process)
  • CODEX_TOOL_NAME Tool name prefix (default: codex)
  • CODEX_MODEL Model: gpt-5-codex, o3, codex-1, or full ID
  • CODEX_SANDBOX_MODE Sandbox: read-only, workspace-write, danger-full-access
  • CODEX_APPROVAL_POLICY Approval: never, on-failure, on-request, untrusted
  • CODEX_APPEND_INSTRUCTIONS Additional instructions appended to the default
  • CODEX_FACTORY_ONLY Set to true to expose only the factory wizard tool

Documentation

From the project's README on GitHub, refreshed weekly. Links open on GitHub.

Contents
  1. Codex Octopus
  2. Why
  3. Prerequisites
  4. Install
  5. Quick Start
  6. Multiple Agents
  7. Agent Factory
  8. Tools
  9. Configuration
  10. Security
  11. Architecture
  12. Known Limitations
  13. Development
  14. License

Codex Octopus

One brain, many arms.

An MCP server that wraps the OpenAI Codex SDK, letting you run multiple specialized Codex agents — each with its own model, sandbox, effort, and personality — from any MCP client.

Why

Codex is powerful. But one instance does everything the same way. Sometimes you want a strict code reviewer in read-only sandbox. A test writer with workspace-write access. A cheap quick helper on minimal effort. A deep thinker on xhigh.

Codex Octopus lets you spin up as many of these as you need. Same binary, different configurations. Each one shows up as a separate tool in your MCP client.

Prerequisites

  • Node.js >= 18
  • Codex CLI — the Codex SDK spawns the Codex CLI under the hood, so you need it installed (@openai/codex)
  • OpenAI API key (CODEX_API_KEY env var) or inherited from parent process

Install

npm install codex-octopus

Or use npx directly in your .mcp.json (see Quick Start below).

Quick Start

Add to your .mcp.json:

{
  "mcpServers": {
    "codex": {
      "command": "npx",
      "args": ["codex-octopus@latest"],
      "env": {
        "CODEX_SANDBOX_MODE": "workspace-write",
        "CODEX_APPROVAL_POLICY": "never"
      }
    }
  }
}

This gives you two tools: codex and codex_reply. That's it — you have Codex as a tool.

Multiple Agents

The real power is running several instances with different configurations:

{
  "mcpServers": {
    "code-reviewer": {
      "command": "npx",
      "args": ["codex-octopus@latest"],
      "env": {
        "CODEX_TOOL_NAME": "code_reviewer",
        "CODEX_SERVER_NAME": "code-reviewer",
        "CODEX_DESCRIPTION": "Strict code reviewer. Read-only sandbox.",
        "CODEX_MODEL": "o3",
        "CODEX_SANDBOX_MODE": "read-only",
        "CODEX_APPEND_INSTRUCTIONS": "You are a strict code reviewer. Report real bugs, not style preferences.",
        "CODEX_EFFORT": "high"
      }
    },
    "test-writer": {
      "command": "npx",
      "args": ["codex-octopus@latest"],
      "env": {
        "CODEX_TOOL_NAME": "test_writer",
        "CODEX_SERVER_NAME": "test-writer",
        "CODEX_DESCRIPTION": "Writes thorough tests with edge case coverage.",
        "CODEX_MODEL": "gpt-5-codex",
        "CODEX_SANDBOX_MODE": "workspace-write",
        "CODEX_APPEND_INSTRUCTIONS": "Write tests first. Cover edge cases. TDD."
      }
    },
    "quick-qa": {
      "command": "npx",
      "args": ["codex-octopus@latest"],
      "env": {
        "CODEX_TOOL_NAME": "quick_qa",
        "CODEX_SERVER_NAME": "quick-qa",
        "CODEX_DESCRIPTION": "Fast answers to quick coding questions.",
        "CODEX_EFFORT": "minimal"
      }
    }
  }
}

Your MCP client now sees three distinct tools — code_reviewer, test_writer, quick_qa — each purpose-built.

Agent Factory

Don't want to write configs by hand? Add a factory instance:

{
  "mcpServers": {
    "agent-factory": {
      "command": "npx",
      "args": ["codex-octopus@latest"],
      "env": {
        "CODEX_FACTORY_ONLY": "true",
        "CODEX_SERVER_NAME": "agent-factory"
      }
    }
  }
}

This exposes a single create_codex_mcp tool — an interactive wizard. Tell it what you want ("a strict code reviewer with read-only sandbox") and it generates the .mcp.json entry for you.

Tools

Each non-factory instance exposes:

ToolPurpose
<name>Send a task to the agent, get a response + thread_id
<name>_replyContinue a previous conversation by thread_id

Per-invocation parameters (override server defaults):

ParameterDescription
promptThe task or question (required)
cwdWorking directory override
modelModel override
additionalDirsExtra directories the agent can access
effortReasoning effort (minimal to xhigh)
sandboxModeSandbox override (can only tighten, never loosen)
approvalPolicyApproval override (can only tighten, never loosen)
networkAccessEnable network access from sandbox
webSearchModeWeb search: disabled, cached, live
instructionsAdditional instructions (prepended to prompt)

Configuration

All configuration is via environment variables in .mcp.json. Every env var is optional.

Identity
Env VarDescriptionDefault
CODEX_TOOL_NAMETool name prefix (<name> and <name>_reply)codex
CODEX_DESCRIPTIONTool description shown to the host AIgeneric
CODEX_SERVER_NAMEMCP server name in protocol handshakecodex-octopus
CODEX_FACTORY_ONLYOnly expose the factory wizard toolfalse
Agent
Env VarDescriptionDefault
CODEX_MODELModel (gpt-5-codex, o3, codex-1, etc.)SDK default
CODEX_CWDWorking directoryprocess.cwd()
CODEX_SANDBOX_MODEread-only, workspace-write, danger-full-accessread-only
CODEX_APPROVAL_POLICYnever, on-failure, on-request, untrustedon-failure
CODEX_EFFORTminimal, low, medium, high, xhighSDK default
CODEX_ADDITIONAL_DIRSExtra directories (comma-separated)none
CODEX_NETWORK_ACCESSAllow network from sandboxfalse
CODEX_WEB_SEARCHdisabled, cached, livedisabled
Instructions
Env VarDescription
CODEX_INSTRUCTIONSReplaces the default instructions
CODEX_APPEND_INSTRUCTIONSAppended to the default (usually what you want)
Advanced
Env VarDescription
CODEX_PERSIST_SESSIONtrue/false — enable session resume (default: true)
Authentication
Env VarDescriptionDefault
CODEX_API_KEYOpenAI API key for this agentinherited from parent

Security

  • Sandbox defaults to read-only — the agent can't write files unless you explicitly set workspace-write or danger-full-access.
  • cwd overrides preserve agent knowledge — when the host overrides cwd, the agent's configured base directory is automatically added to additionalDirectories.
  • Security overrides narrow, never widen — per-invocation sandboxMode and approvalPolicy can only tighten (e.g., workspace-write → read-only), never loosen.
  • _reply tool respects persistence — not registered when CODEX_PERSIST_SESSION=false.
  • API keys are redacted — the factory wizard never exposes CODEX_API_KEY in generated configs.

Architecture

┌─────────────────────────────────┐
│  MCP Client                     │
│  (Claude Desktop, Cursor, etc.) │
│                                 │
│  Sees: code_reviewer,           │
│        test_writer, quick_qa    │
└──────────┬──────────────────────┘
           │ JSON-RPC / stdio
┌──────────▼──────────────────────┐
│  Codex Octopus (per instance)   │
│                                 │
│  Env: CODEX_MODEL=o3            │
│       CODEX_SANDBOX_MODE=...    │
│       CODEX_APPEND_INSTRUCTIONS │
│                                 │
│  Calls: Codex SDK thread.run()  │
└──────────┬──────────────────────┘
           │ in-process
┌──────────▼──────────────────────┐
│  Codex SDK → Codex CLI          │
│  Runs autonomously: reads files,│
│  writes code, runs commands     │
│  Returns result + thread_id     │
└─────────────────────────────────┘

Known Limitations

  • minimal effort + web_search: OpenAI does not allow web_search tools with minimal reasoning effort. Use low or higher if web search is needed.

Development

pnpm install
pnpm build       # compile TypeScript
pnpm test        # run tests (vitest)
pnpm test:coverage  # coverage report

License

ISC - Xiaolai Li

Frequently asked questions

What is io.github.xiaolai/codex-octopus?

Spawn multiple specialized Codex agents as MCP servers, each independently configured.

How do I install io.github.xiaolai/codex-octopus?

It runs on your machine. In Claude Code: claude mcp add codex-octopus -e 'CODEX_API_KEY=<your codex_api_key>' -e 'CODEX_TOOL_NAME=<CODEX_TOOL_NAME>' -e 'CODEX_MODEL=<CODEX_MODEL>' -e 'CODEX_SANDBOX_MODE=<CODEX_SANDBOX_MODE>' -e 'CODEX_APPROVAL_POLICY=<CODEX_APPROVAL_POLICY>' -e 'CODEX_APPEND_INSTRUCTIONS=<CODEX_APPEND_INSTRUCTIONS>' -e 'CODEX_FACTORY_ONLY=<CODEX_FACTORY_ONLY>' -- npx -y codex-octopus@1.0.1. For other clients, paste the JSON configuration from this page into their MCP settings.

Does io.github.xiaolai/codex-octopus need an API key?

Yes. It expects CODEX_API_KEY, which you set in its configuration.

Is io.github.xiaolai/codex-octopus open source?

Yes. Its code is on GitHub under the ISC license.

Who maintains io.github.xiaolai/codex-octopus?

It is published by xiaolai. AI.tn lists it but does not maintain or endorse it.

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