What problem does MCP-Codex solve?
Traditional MCP implementations require static configuration and restarting the assistant when adding new tools. MCP-Codex enables dynamic discovery and execution, reducing operational complexity.
@twolven
基本情報
A MCP server for calling MCP tools remotely without requiring installation.
以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。
{
"mcpServers": {
"mcp-codex": {
"command": "python",
"args": [
"codex-serv.py"
]
}
}
}ツール一覧はまだありません
この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。
ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。
MCP-Codex is a service for orchestrating Model Context Protocol (MCP) servers, allowing AI assistants to dynamically discover and utilize tools without requiring restarts. It features “The Librarian,” an intelligent agent that understands user needs and connects them with the right tools. This project is discontinued and shared as an educational resource.
Install by cloning the repository, running pip install -r requirements.txt, creating config, data, logs, tools directories, and configuring the .env file. Start the Codex Service with python codex-serv.py and the MCP Client with python mcp-codex.py. For Claude Desktop, use mcp install mcp-codex.py. The client registers two tools: search (find tools for a task) and call_tool (execute discovered tools).
Traditional MCP implementations require static configuration and restarting the assistant when adding new tools. MCP-Codex enables dynamic discovery and execution, reducing operational complexity.
The project consists of the Codex Service (core execution), the Librarian Service (planned AI-powered tool recommendation), and the MCP Client (interface for AI assistants).
The AI assistant uses the `search` tool to find relevant capabilities via natural language, then executes the discovered tool through the `call_tool` tool, which the Codex Service handles.
No. This project was discontinued after Cloudflare released a similar service. The code is shared as an educational resource and example of MCP orchestration architecture.
Python 3.10+ and required packages from `requirements.txt`. The tool registry is configured in `config/codex.yaml` and the environment via a `.env` file.
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