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Codex Bridge

by eLyiN
GitHub
Python
MIT License
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Codex Bridge

CI Status PyPI Version MIT License Python 3.10+ MCP Compatible Codex CLI

A lightweight MCP (Model Context Protocol) server that enables AI coding assistants to interact with OpenAI's Codex AI through the official CLI. Works with Claude Code, Cursor, VS Code, and other MCP-compatible clients. Designed for simplicity, reliability, and seamless integration.

✨ Features

  • Direct Codex CLI Integration: Zero API costs using official Codex CLI
  • Simple MCP Tools: Two core functions for basic queries and file analysis
  • Stateless Operation: No sessions, caching, or complex state management
  • Production Ready: Robust error handling with configurable timeouts (default: 90 seconds)
  • Minimal Dependencies: Only requires mcp>=1.0.0 and Codex CLI
  • Easy Deployment: Support for both uvx and traditional pip installation
  • Universal MCP Compatibility: Works with any MCP-compatible AI coding assistant

🚀 Quick Start

Prerequisites

  1. Install Codex CLI:
    npm install -g @openai/codex-cli
  2. Authenticate with Codex:
    codex
  3. Verify installation:
    codex --version

Installation

🎯 Recommended: PyPI Installation

# Install from PyPI pip install codex-bridge # Add to Claude Code with uvx (recommended) claude mcp add codex-bridge -s user -- uvx codex-bridge

Alternative: From Source

# Clone the repository git clone https://github.com/shelakh/codex-bridge.git cd codex-bridge # Build and install locally uvx --from build pyproject-build pip install dist/*.whl # Add to Claude Code claude mcp add codex-bridge -s user -- uvx codex-bridge

Development Installation

# Clone and install in development mode git clone https://github.com/shelakh/codex-bridge.git cd codex-bridge pip install -e . # Add to Claude Code (development) claude mcp add codex-bridge-dev -s user -- python -m src

🌐 Multi-Client Support

Codex Bridge works with any MCP-compatible AI coding assistant - the same server supports multiple clients through different configuration methods.

Supported MCP Clients

  • Claude Code ✅ (Default)
  • Cursor ✅
  • VS Code ✅
  • Windsurf ✅
  • Cline ✅
  • Void ✅
  • Cherry Studio ✅
  • Augment ✅
  • Roo Code ✅
  • Zencoder ✅
  • Any MCP-compatible client ✅

Configuration Examples

# Recommended installation claude mcp add codex-bridge -s user -- uvx codex-bridge # Development installation claude mcp add codex-bridge-dev -s user -- python -m src

Global Configuration (~/.cursor/mcp.json):

{ "mcpServers": { "codex-bridge": { "command": "uvx", "args": ["codex-bridge"], "env": {} } } }

Project-Specific (.cursor/mcp.json in your project):

{ "mcpServers": { "codex-bridge": { "command": "uvx", "args": ["codex-bridge"], "env": {} } } }

Go to: Settings → Cursor Settings → MCP → Add new global MCP server

Configuration (.vscode/mcp.json in your workspace):

{ "servers": { "codex-bridge": { "type": "stdio", "command": "uvx", "args": ["codex-bridge"] } } }

Alternative: Through Extensions

  1. Open Extensions view (Ctrl+Shift+X)
  2. Search for MCP extensions
  3. Add custom server with command: uvx codex-bridge

Add to your Windsurf MCP configuration:

{ "mcpServers": { "codex-bridge": { "command": "uvx", "args": ["codex-bridge"], "env": {} } } }
  1. Open Cline and click MCP Servers in the top navigation
  2. Select Installed tab → Advanced MCP Settings
  3. Add to cline_mcp_settings.json:
{ "mcpServers": { "codex-bridge": { "command": "uvx", "args": ["codex-bridge"], "env": {} } } }

Go to: Settings → MCP → Add MCP Server

{ "mcpServers": { "codex-bridge": { "command": "uvx", "args": ["codex-bridge"], "env": {} } } }
  1. Navigate to Settings → MCP Servers → Add Server
  2. Fill in the server details:
    • Name: codex-bridge
    • Type: STDIO
    • Command: uvx
    • Arguments: ["codex-bridge"]
  3. Save the configuration

Using the UI:

  1. Click hamburger menu → Settings → Tools
  2. Click + Add MCP button
  3. Enter command: uvx codex-bridge
  4. Name: Codex Bridge

Manual Configuration:

"augment.advanced": { "mcpServers": [ { "name": "codex-bridge", "command": "uvx", "args": ["codex-bridge"], "env": {} } ] }
  1. Go to Settings → MCP Servers → Edit Global Config
  2. Add to mcp_settings.json:
{ "mcpServers": { "codex-bridge": { "command": "uvx", "args": ["codex-bridge"], "env": {} } } }
  1. Go to Zencoder menu (...) → Tools → Add Custom MCP
  2. Add configuration:
{ "command": "uvx", "args": ["codex-bridge"], "env": {} }
  1. Hit the Install button

For pip-based installations:

{ "command": "codex-bridge", "args": [], "env": {} }

For development/local testing:

{ "command": "python", "args": ["-m", "src"], "env": {}, "cwd": "/path/to/codex-bridge" }

For npm-style installation (if needed):

{ "command": "npx", "args": ["codex-bridge"], "env": {} }

Universal Usage

Once configured with any client, use the same two tools:

  1. Ask general questions: "What authentication patterns are used in this codebase?"
  2. Analyze specific files: "Review these auth files for security issues"

The server implementation is identical - only the client configuration differs!

⚙️ Configuration

Timeout Configuration

By default, Codex Bridge uses a 90-second timeout for all CLI operations. For longer queries (large files, complex analysis), you can configure a custom timeout using the CODEX_TIMEOUT environment variable.

Example configurations:

# Add with custom timeout (120 seconds) claude mcp add codex-bridge -s user --env CODEX_TIMEOUT=120 -- uvx codex-bridge
{ "mcpServers": { "codex-bridge": { "command": "uvx", "args": ["codex-bridge"], "env": { "CODEX_TIMEOUT": "120" } } } }

Timeout Options:

  • Default: 90 seconds (if not configured)
  • Range: Any positive integer (seconds)
  • Recommended: 60-120 seconds for most queries, 120-300 for large file analysis
  • Invalid values: Fall back to 90 seconds with warning

🛠️ Available Tools

consult_codex

Direct CLI bridge for simple queries with structured JSON output by default.

Parameters:

  • query (string): The question or prompt to send to Codex
  • directory (string): Working directory for the query (default: current directory)
  • format (string): Output format - "text", "json", or "code" (default: "json")
  • timeout (int, optional): Timeout in seconds (recommended: 60-120, default: 90)

Example:

consult_codex( query="Find authentication patterns in this codebase", directory="/path/to/project", format="json", # Default format timeout=90 # Default timeout )

consult_codex_with_stdin

CLI bridge with stdin content for pipeline-friendly execution.

Parameters:

  • stdin_content (string): Content to pipe as stdin (file contents, diffs, logs)
  • prompt (string): The prompt to process the stdin content
  • directory (string): Working directory for the query
  • format (string): Output format - "text", "json", or "code" (default: "json")
  • timeout (int, optional): Timeout in seconds (recommended: 60-120, default: 90)

consult_codex_batch

Batch processing for multiple queries - perfect for CI/CD automation.

Parameters:

  • queries (list): List of query dictionaries with 'query' and optional 'timeout'
  • directory (string): Working directory for all queries
  • format (string): Output format - currently only "json" supported for batch

Example:

consult_codex_with_stdin( stdin_content=open("src/auth.py").read(), prompt="Analyze this auth file and suggest improvements", directory="/path/to/project", format="json", # Default format timeout=120 # Custom timeout for complex analysis )

📋 Usage Examples

Basic Code Analysis

# Simple research query consult_codex( query="What authentication patterns are used in this project?", directory="/Users/dev/my-project" )

Detailed File Review

# Analyze specific files with open("/Users/dev/my-project/src/auth.py") as f: auth_content = f.read() consult_codex_with_stdin( stdin_content=auth_content, prompt="Review this file and suggest security improvements", directory="/Users/dev/my-project", format="json", # Structured output timeout=120 # Allow more time for detailed analysis )

Batch Processing

# Process multiple queries at once consult_codex_batch( queries=[ {"query": "Analyze authentication patterns", "timeout": 60}, {"query": "Review database implementations", "timeout": 90}, {"query": "Check security vulnerabilities", "timeout": 120} ], directory="/Users/dev/my-project", format="json" # Always JSON for batch processing )

🏗️ Architecture

Core Design

  • CLI-First: Direct subprocess calls to codex command
  • Stateless: Each tool call is independent with no session state
  • Configurable Timeout: 90-second default execution time (configurable)
  • Structured Output: JSON format by default for better integration
  • Simple Error Handling: Clear error messages with fail-fast approach

Project Structure

codex-bridge/ ├── src/ │ ├── __init__.py # Entry point │ ├── __main__.py # Module execution entry point │ └── mcp_server.py # Main MCP server implementation ├── .github/ # GitHub templates and workflows ├── pyproject.toml # Python package configuration ├── README.md # This file ├── CONTRIBUTING.md # Contribution guidelines ├── CODE_OF_CONDUCT.md # Community standards ├── SECURITY.md # Security policies ├── CHANGELOG.md # Version history └── LICENSE # MIT license

🔧 Development

Local Testing

# Install in development mode pip install -e . # Run directly python -m src # Test CLI availability codex --version

Integration with Claude Code

The server automatically integrates with Claude Code when properly configured through the MCP protocol.

🔍 Troubleshooting

CLI Not Available

# Install Codex CLI npm install -g @openai/codex-cli # Authenticate codex auth login # Test codex --version

Connection Issues

  • Verify Codex CLI is properly authenticated
  • Check network connectivity
  • Ensure Claude Code MCP configuration is correct
  • Check that the codex command is in your PATH

Common Error Messages

  • "CLI not available": Codex CLI is not installed or not in PATH
  • "Authentication required": Run codex auth login
  • "Timeout after X seconds": Query took too long, try increasing timeout or breaking into smaller parts

🤝 Contributing

We welcome contributions from the community! Please read our Contributing Guidelines for details on how to get started.

Quick Contributing Guide

  1. Fork the repository
  2. Create a feature branch
  3. Make your changes
  4. Add tests if applicable
  5. Submit a pull request

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🔄 Version History

See CHANGELOG.md for detailed version history.

🆘 Support

  • Issues: Report bugs or request features via GitHub Issues
  • Discussions: Join the community discussion
  • Documentation: Additional docs can be created in the docs/ directory

Focus: A simple, reliable bridge between Claude Code and Codex AI through the official CLI.

This server cannot be installed

-
security - not tested
A
license - permissive license
-
quality - not tested

How are these scores calculated?

local-only server

The server can only run on the client's local machine because it depends on local resources.

Enables AI coding assistants to interact with OpenAI's Codex AI through the official CLI. Provides direct integration for code analysis, file review, and batch processing with zero API costs.

  1. ✨ Features
    1. 🚀 Quick Start
      1. Prerequisites
      2. Installation
    2. 🌐 Multi-Client Support
      1. Supported MCP Clients
      2. Configuration Examples
      3. Universal Usage
    3. ⚙️ Configuration
      1. Timeout Configuration
    4. 🛠️ Available Tools
      1. consult_codex
      2. consult_codex_with_stdin
      3. consult_codex_batch
    5. 📋 Usage Examples
      1. Basic Code Analysis
      2. Detailed File Review
      3. Batch Processing
    6. 🏗️ Architecture
      1. Core Design
      2. Project Structure
    7. 🔧 Development
      1. Local Testing
      2. Integration with Claude Code
    8. 🔍 Troubleshooting
      1. CLI Not Available
      2. Connection Issues
      3. Common Error Messages
    9. 🤝 Contributing
      1. Quick Contributing Guide
    10. 📄 License
      1. 🔄 Version History
        1. 🆘 Support

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