Claude Code Companion: The Complete Guide to Stable and Flexible AI API Management

Introduction

In the rapidly evolving world of artificial intelligence, having reliable access to large language models has become crucial for developers and researchers alike. Today, we’re exploring a powerful tool called “Claude Code Companion” that significantly enhances your experience with Claude Code. Whether you’re new to AI or an experienced developer, this tool provides a more stable and flexible way to connect to AI services.

What is Claude Code Companion?

Claude Code Companion is a local API proxy tool specifically designed for Claude Code. Its core value lies in intelligently managing multiple upstream service endpoints, validating response formats, and automatically switching endpoints when necessary. This dramatically improves the stability and observability of your proxy service.

Perhaps most impressively, it offers a complete web management interface that allows even beginners to get started quickly and maintain the system efficiently. This means you no longer need to navigate complex command-line configurations but can instead manage everything through an intuitive graphical interface.

Detailed Explanation of Core Features

Multi-Endpoint Load Balancing and Failover

In practical use, we often encounter situations where single service endpoints become unstable or completely unavailable. Claude Code Companion addresses this issue by supporting configuration of multiple upstream service endpoints and attempting connections according to preset priorities, automatically switching when endpoints become unavailable.

How it works:

  • You can configure multiple service endpoint information
  • The system attempts connections in your specified priority order
  • When an endpoint becomes unavailable, it automatically switches to the next available one
  • The entire process is completely transparent to users, requiring no manual intervention

Response Format Validation Mechanism

Data format consistency is crucial in API interactions. Claude Code Companion includes built-in response format validation that checks whether data returned from upstream services meets Anthropic protocol requirements.

When abnormal responses are detected, the system automatically disconnects the current connection and triggers a reconnection mechanism, ensuring you always receive data responses in the expected format.

OpenAI-Compatible Node Access

This feature significantly expands the application scope of Claude Code Companion. Through the “OpenAI compatible” type, you can connect various models like GPT5, GLM, and K2 for use with Claude Code.

This means you’re no longer limited to a single model service but can choose the most suitable AI model based on your specific needs, greatly enhancing the tool’s flexibility and practicality.

Intelligent Fault Detection and Recovery

The system can automatically flag abnormal endpoints and continuously monitor their recovery status in the background. Once previously unavailable endpoints return to normal, they are automatically reintroduced into the available endpoint pool, achieving fully automatic fault recovery.

Smart Label Routing Function

Dynamic routing rules based on request paths, headers, or content represent another highlight of Claude Code Companion. The ability to select endpoints by label enables intelligent distribution of requests to the most appropriate service endpoints based on different application scenarios.

Complete Request Logging and Visual Management

The system maintains complete request/response logs and provides a web interface for endpoint management, log viewing, and system monitoring. This not only facilitates daily maintenance but also provides detailed data support for troubleshooting.

How to Get Started? – Detailed Step-by-Step Guide

Step 1: Download and Installation

  1. Visit the project’s Release page and locate the compressed package for your operating system (supports Linux and Windows systems)
  2. Download the compressed package to your local machine
  3. Extract the compressed files to your chosen directory
  4. Open terminal or command line interface and navigate to the extracted directory

Step 2: Initial Operation and Configuration

  1. Execute the program directly (run the binary file on Linux, or the corresponding executable on Windows)
  2. The program will automatically generate a default config.yaml file in the current directory
  3. This configuration file contains all adjustable parameter settings that you can modify as needed later

Step 3: Accessing the Management Interface

  1. Open your web browser
  2. Enter in the address bar: http://localhost:8080/admin
  3. You will see Claude Code Companion’s web management interface

This management interface is intuitively designed with four main functional areas:

  • Endpoint configuration management
  • Label rule settings
  • Request log viewing
  • System monitoring and settings

Step 4: Adding Upstream Endpoints

  1. Navigate to the “Admin → Endpoints” section in the management interface
  2. Click the “Add New” button
  3. Fill in the upstream service URL address
  4. Enter the appropriate authentication information
  5. Select the endpoint type (Anthropic or OpenAI compatible)
  6. Save your settings

Practical tip: You can adjust endpoint priorities by dragging and dropping, with all operations taking effect immediately without requiring service restart.

Step 5: Configuring Claude Code to Use the Proxy Service

To make Claude Code use the Claude Code Companion proxy, you need to set the following environment variables:

# Point ANTHROPIC_BASE_URL to the proxy address
export ANTHROPIC_BASE_URL="http://localhost:8080/"

# Set authentication token (can be any value, but cannot be empty)
export ANTHROPIC_AUTH_TOKEN="your_token_here"

# Set API timeout to ensure proxy client doesn't timeout when account pools timeout
export API_TIMEOUT_MS=600000

# Recommended setting to avoid non-essential traffic transmission
export CLAUDE_CODE_DISABLE_NONESSENTIAL_TRAFFIC=1

Detailed Common Usage Scenarios

Scenario 1: Automatic Switching Between Multiple Account Pools

This is the most typical application scenario for Claude Code Companion. When you have multiple service account pools, configure them as follows:

  1. Collect endpoint information provided by each account pool (most account pools in the market use Auth Token authentication except GAC which uses API key authentication)
  2. Add these endpoint information sequentially to Claude Code Companion’s endpoint list
  3. The system will automatically attempt connections to each endpoint in your specified order
  4. When an endpoint fails, it automatically switches to the next available one

Operation tip: You can adjust endpoint attempt order through simple drag-and-drop operations, with all adjustments taking effect immediately without service restart.

Scenario 2: Using Third-Party Model Services

Another significant advantage of Claude Code Companion is its ability to integrate various third-party model services:

For models providing Anthropic-type endpoints (such as GLM and K2):

  1. Add these model endpoints like regular account pools
  2. Drag them to the highest priority position
  3. After saving settings, Claude Code will start using this model service

For services only providing OpenAI-compatible access (such as openrouter or Volcano Qianwen):

  1. Select “OpenAI compatible” type when adding endpoints
  2. Set the default model to your desired specific model name
  3. Drag this endpoint to the highest priority position
  4. After saving, Claude Code can use these third-party models through the proxy

Technical Details and Best Practices

In-Depth Understanding of Configuration Files

The config.yaml file generated when you first run Claude Code Companion contains all configurable parameters. While the default configuration suits most usage scenarios, understanding the main parameters will help you better customize the service:

  • Port settings: Default uses port 8080, which you can modify as needed
  • Timeout settings: Reasonably configure connection and read timeout durations
  • Log level: Adjust log detail level according to debugging needs
  • Endpoint health checks: Configure health check intervals and timeout settings

Performance Optimization Recommendations

  1. Connection pool configuration: Adjust connection pool size appropriately based on your concurrent needs
  2. Caching strategy: Implement caching for frequently requested data
  3. Load testing: Conduct thorough load testing before production deployment
  4. Monitoring alerts: Set up system monitoring and exception alert mechanisms

Troubleshooting and Common Questions

Q: Why can’t my Claude Code connect to the proxy service?

A: Please check the following aspects:

  • Confirm whether the proxy service started normally
  • Check if port 8080 is occupied by other programs
  • Verify whether the ANTHROPIC_BASE_URL environment variable is set correctly

Q: How to confirm endpoints were added successfully and are working properly?

A: You can verify through the following methods:

  • Check endpoint status in the “Endpoints” section of the web management interface
  • Examine the health status indicators of endpoints
  • Review request logs to confirm if traffic is passing through the endpoint

Q: Why is API_TIMEOUT_MS=600000 necessary?

A: This setting ensures that when upstream services respond slowly, the Claude Code client won’t timeout before the proxy. The 600000 millisecond (10-minute) timeout provides sufficient time buffer for most complex tasks.

Q: What does the CLAUDE_CODE_DISABLE_NONESSENTIAL_TRAFFIC setting do?

A: This setting reduces the non-essential data that Claude Code sends to its company servers, protecting privacy and potentially improving performance.

Advanced Configuration Techniques

Custom Routing Rules

For advanced users, Claude Code Companion offers sophisticated routing capabilities:

Path-based routing:

  • Direct specific API paths to designated endpoints
  • Useful for separating different types of requests
  • Can optimize performance by routing to specialized endpoints

Content-based routing:

  • Route requests based on content characteristics
  • Particularly useful for multi-model environments
  • Ensures optimal model selection for each query type

Security Considerations

When deploying Claude Code Companion in production environments, consider these security aspects:

Authentication management:

  • Regularly rotate API keys and tokens
  • Use environment variables for sensitive information
  • Implement proper access controls

Network security:

  • Consider deploying behind a firewall
  • Use HTTPS for all communications
  • Monitor for unusual access patterns

Performance Monitoring and Optimization

Key Metrics to Monitor

To maintain optimal performance, keep an eye on these critical metrics:

Endpoint health metrics:

  • Response times across different endpoints
  • Success and failure rates
  • Automatic failover frequency

System performance indicators:

  • Memory and CPU usage
  • Network bandwidth consumption
  • Connection pool utilization

Optimization Strategies

Based on performance monitoring data, consider these optimization approaches:

Load distribution:

  • Distribute requests based on endpoint capabilities
  • Implement weighted routing for heterogeneous endpoints
  • Consider geographical distribution for global services

Caching implementation:

  • Cache frequent identical requests
  • Implement appropriate cache expiration policies
  • Monitor cache hit rates for effectiveness

Conclusion

Claude Code Companion stands as a powerful API proxy tool that significantly enhances the stability and flexibility of using Claude Code through its multi-endpoint management, automatic failover, and response validation capabilities. Whether managing multiple account pools or integrating third-party model services, it provides simple yet efficient solutions.

Most commendable is its intuitive web management interface, which allows even users unfamiliar with command-line operations to get started easily. Through this detailed guide, we believe you’ve gained comprehensive understanding of how to install, configure, and use this tool.

In practical use, we recommend starting with simple configurations and gradually adding more endpoints and adjusting parameters based on needs. Remember to regularly check system logs and endpoint status to ensure services remain in optimal operating condition.

As artificial intelligence technology continues to develop, tools like Claude Code Companion will become increasingly important. They help us enjoy the conveniences of AI while ensuring service stability and reliability. We hope this article provides practical guidance for using this tool and wish you great success in your AI exploration journey!