codex-multi-model-workers
Allows connecting to OpenAI-compatible Chat Completions endpoints, enabling read-only worker analysis and implementation proposals routed through Codex.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@codex-multi-model-workersconfigure the official DeepSeek API with model deepseek-chat"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Codex Multi-Model Workers
A distributable Codex plugin that connects Codex to local and cloud language models through a controlled MCP worker boundary.
Supported providers:
MoE4All local GGUF servers
GLM official cloud API and custom compatible endpoints
DeepSeek official cloud API and custom compatible endpoints
Generic OpenAI-compatible Chat Completions endpoints
Codex remains the controller. Workers return analysis, implementation proposals, or patch text and never receive direct write authority over the main working tree.
Requirements
A Codex build with plugin marketplace support
Node.js 20 or newer available as
nodeProvider credentials in environment variables when cloud APIs are used
MoE4All and a GGUF model already downloaded when local inference is used
The committed MCP bundle is self-contained. End users do not run npm install.
Related MCP server: Brooks Model MCP
Install
Add this Git repository as a Codex marketplace:
codex plugin marketplace add aaa17001/codex-multi-model-workersInstall the plugin:
codex plugin add codex-multi-model-workers@multi-model-workersStart a new Codex task so the Skill and MCP tools are discovered. Invoke the Skill as $multi-model-workers in CLI/IDE environments or @multi-model-workers where the Codex app exposes Skills with @.
Secrets
Set API keys in the environment that launches Codex. Do not put key values in provider JSON, prompts, repository files, or VS Code configuration.
PowerShell current session:
$env:GLM_API_KEY = 'your-key'
$env:DEEPSEEK_API_KEY = 'your-key'
$env:MOE4ALL_API_KEY = 'your-optional-local-key'Bash current session:
export GLM_API_KEY='your-key'
export DEEPSEEK_API_KEY='your-key'
export MOE4ALL_API_KEY='your-optional-local-key'GLM also recognizes ZAI_API_KEY when the configured name is GLM_API_KEY and that variable is absent.
The plugin MCP explicitly forwards these variable names from Codex: GLM_API_KEY, ZAI_API_KEY,
DEEPSEEK_API_KEY, MOE4ALL_API_KEY, OPENAI_API_KEY, TEAM_GLM_API_KEY,
TEAM_DEEPSEEK_API_KEY, and TEAM_MODEL_API_KEY. Set apiKeyEnv to one of these names. Values are
never stored in the plugin manifest.
Configure Providers
Ask the Skill to configure only the provider you need:
Use $multi-model-workers to configure the official DeepSeek API with model deepseek-chat.Use $multi-model-workers to configure a custom GLM-compatible endpoint at https://gateway.example.com/glm/v1.Configuration tools accept apiKeyEnv, which is an environment variable name. They reject literal apiKey, token, secret, and password fields.
Default non-secret configuration locations:
Windows:
%APPDATA%\codex-multi-model-workers\config.jsonmacOS/Linux:
${XDG_CONFIG_HOME:-~/.config}/codex-multi-model-workers/config.jsonOverride:
CODEX_MULTI_MODEL_CONFIG
See providers.example.json and the Provider reference.
MoE4All
MoE4All paths are machine-specific and are never hard-coded by the plugin. Configure absolute paths, loopback host, port, and the model id exposed by the server:
Use $multi-model-workers to configure MoE4All with infr.exe at D:\Tools\MoE4All\infr.exe and model D:\Models\model.gguf. Bind 127.0.0.1:8080 and enable --think.Then ask the Skill to start the configured provider. The plugin:
refuses non-loopback managed launches
passes arguments without a shell
keeps the API key out of process arguments
records the owned PID only after
/healthsucceedsrefuses to stop a PID whose command line no longer matches both configured paths
The plugin does not download MoE4All or GGUF files.
Route And Ask Workers
Use $multi-model-workers to recommend a worker for scanning this repository.route_task is advisory and sends no task content. After reviewing the recommendation, ask the selected worker explicitly:
Use $multi-model-workers to ask local-moe to analyze this log. Do not modify files.High-risk, architecture, security, cross-module, and final-review work remains with Codex.
VS Code
After configuring providers:
Use $multi-model-workers to add local-moe, glm, and deepseek to my VS Code language models.The plugin merges provider groups into chatLanguageModels.json, preserves unrelated groups, and creates a timestamped backup. Generated entries use explicit Chat Completions URLs and VS Code ${input:...} secret references.
VS Code is only an API client. Its model configuration does not start infr.exe or load a GGUF model.
Tools
Tool | Purpose |
| List non-secret configuration and credential availability. |
| Probe one provider with a bounded timeout. |
| Persist non-secret settings after confirmation. |
| Request read-only worker analysis. |
| Recommend a target without sending the task. |
| Start a loopback-only local server after confirmation. |
| Stop a verified plugin-owned process after confirmation. |
| Back up and merge VS Code model entries after confirmation. |
Development
npm ci --prefix plugins/codex-multi-model-workers/mcp
npm testnpm test rebuilds the committed self-contained MCP bundle and runs the full test suite, including a stdio acceptance test from an isolated directory with no node_modules.
See CONTRIBUTING.md, SECURITY.md, and the design.
License
MIT
This server cannot be deployed
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