Codex CLI v0.50.0+ Integration Guide
Overview
This document outlines the integration with OpenAI Codex CLI v0.50.0+, highlighting breaking changes, new features, and implementation details for the MCP server wrapper.
Version Compatibility
Minimum Version: v0.50.0
This MCP server requires codex CLI v0.50.0 or later due to critical flag changes.
Version History:
v0.50.0: Introduced
--skip-git-repo-checkflag, removed--reasoning-effortflagv0.36.0-v0.49.x: Not compatible with this MCP server version (use older MCP releases)
Breaking Changes ⚠️
v0.50.0 Changes (Current)
--skip-git-repo-checkflag now requiredRequired when running outside git repositories or in untrusted directories
Prevents "Not inside a trusted directory" errors
Impact: All MCP server commands now include this flag
--reasoning-effortflag removedThe flag no longer exists in codex CLI v0.50.0
MCP server
reasoningEffortparameter is now ignoredImpact: Reasoning effort configuration moved to codex CLI's own config
v0.36.0 Changes (Historical)
Authentication Method Change
Old Method:
OPENAI_API_KEYenvironment variableNew Method:
codex login --api-key "your-api-key"Storage: Credentials now stored in
CODEX_HOME/auth.jsonImpact: Users must re-authenticate using the new login command
New Features Implemented
1. Model Selection
Default Model:
gpt-5-codex(optimal for coding tasks)CLI Flag:
--model <model-name>Supported Models:
gpt-5-codex(default, specialized for coding)gpt-4(advanced reasoning)gpt-3.5-turbo(fast responses)
Usage: Model parameter available in both
execandresumemodes
2. Reasoning Effort Control (Deprecated in v0.50.0)
Status: ⚠️ Removed in codex CLI v0.50.0
Previous Flag:
--reasoning-effort <level>(no longer supported)Current Configuration: Set reasoning effort in
~/.codex/config.toml:model_reasoning_effort = "medium" # Options: low, medium, highMCP Parameter: The
reasoningEffortparameter in MCP tool calls is now ignoredMigration: Users should configure reasoning effort directly in codex CLI config
3. Native Resume Functionality
Command:
codex resume <conversation-id>Automatic ID Extraction: Server extracts conversation IDs from CLI output
Regex Pattern:
/conversation\s*id\s*:\s*([a-zA-Z0-9-]+)/iFallback Strategy: Manual context building when resume unavailable
Session Integration: Seamless integration with session management
Implementation Details
Command Construction (v0.50.0+)
// Basic execution (v0.50.0+)
['exec', '--model', selectedModel, '--skip-git-repo-check', prompt]
// Resume with parameters (v0.50.0+)
['resume', conversationId, '--model', selectedModel, '--skip-git-repo-check', prompt]
// Old command structure (v0.36.0-v0.49.x) - NO LONGER SUPPORTED
// ['exec', '--model', selectedModel, '--reasoning-effort', effort, prompt]Key Changes in v0.50.0:
Added:
--skip-git-repo-checkflag (always included)Removed:
--reasoning-effortflag (configure in~/.codex/config.tomlinstead)
Conversation ID Extraction
const conversationIdMatch = result.stderr?.match(/conversation\s*id\s*:\s*([a-zA-Z0-9-]+)/i);
if (conversationIdMatch) {
sessionStorage.setCodexConversationId(sessionId, conversationIdMatch[1]);
}Error Handling Enhancements
Authentication Errors: Clear messaging for login requirement
Model Validation: Graceful handling of invalid model names
Network Issues: Proper error propagation and user feedback
CLI Availability: Detection of missing Codex CLI installation
Migration Guide
For Existing Users (Upgrading to v0.50.0+)
Check Current Version:
codex --versionUpdate Codex CLI (if below v0.50.0):
npm update -g @openai/codex # or brew upgrade codexVerify Version (must be v0.50.0 or later):
codex --version # Should show v0.50.0 or higherUpdate Reasoning Effort Configuration (if used):
# Edit ~/.codex/config.toml # Add or update: model_reasoning_effort = "medium"Test Installation:
codex exec --skip-git-repo-check "console.log('Hello, Codex!')"
For New Users
Install Codex CLI (v0.50.0+):
npm install -g @openai/codex # or brew install codexVerify Version:
codex --version # Must be v0.50.0 or laterAuthenticate:
codex login --api-key "your-openai-api-key"Configure (Optional):
# Edit ~/.codex/config.toml to set preferences # Example: # model = "gpt-5-codex" # model_reasoning_effort = "medium"Test Setup:
codex exec --skip-git-repo-check "console.log('Hello, Codex!')"
Performance Optimizations
Smart Model Selection
Default to gpt-5-codex: Optimal for coding without configuration
Context-Aware Suggestions: Better model recommendations based on task type
Consistent Experience: Same model across session interactions
Efficient Context Management
Native Resume Priority: Use Codex's built-in conversation continuity
Fallback Context: Only when native resume unavailable
Token Optimization: Minimal context overhead for better performance
Error Recovery
Graceful Degradation: Continue operation despite CLI issues
Automatic Retry: For transient network issues
Clear Error Messages: Actionable feedback for user troubleshooting
Testing Strategy
Integration Testing
CLI Command Validation: Verify correct parameter passing
Conversation ID Extraction: Test various output formats
Error Scenario Handling: Comprehensive failure mode coverage
Edge Case Coverage
Malformed CLI Output: Handle unexpected response formats
Network Interruptions: Graceful handling of connectivity issues
Model Availability: Handle model deprecation or unavailability
Best Practices
For Developers
Always specify model explicitly when behavior consistency is critical
Use appropriate reasoning effort based on task complexity
Implement proper error handling for CLI interactions
Monitor session lifecycle to prevent memory leaks
For Users
Start with default settings for optimal experience
Use sessions for complex tasks requiring multiple interactions
Choose reasoning effort wisely to balance speed and quality
Keep CLI updated for latest features and bug fixes
Troubleshooting
Common Issues
Authentication Failures
Solution: Run
codex login --api-key "your-key"Verify: Check
CODEX_HOME/auth.jsonexists
Model Not Available
Solution: Use default
gpt-5-codexor try alternative modelsCheck: Codex CLI documentation for available models
Resume Functionality Not Working
Solution: System falls back to manual context building
Check: Conversation ID extraction in server logs
Performance Issues
Solution: Lower reasoning effort or use faster models
Monitor: Response times and adjust parameters accordingly
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