Claude Code Hub is a modern Claude Code API proxy service that provides intelligent load balancing, user management, and usage statistics. It is designed for teams and enterprises that need to manage multiple AI service providers. The service can be integrated with existing workflows and tools to streamline AI service management.
git clone https://github.com/zsio/claude-code-hub.gitClaude Code Hub is a modern Claude Code API proxy service that provides intelligent load balancing, user management, and usage statistics. It is designed for teams and enterprises that need to manage multiple AI service providers. The service can be integrated with existing workflows and tools to streamline AI service management.
["Identify the specific action you need to perform (e.g., load balancing, user management, or usage tracking) and note the required parameters.","Construct the API call using the Claude Code Hub endpoint. For example, use `POST /api/v1/balance` for load balancing or `GET /api/v1/usage` for statistics.","Include authentication details (API key or token) in the headers. Example: `Authorization: Bearer YOUR_API_KEY`.","Execute the API call using a tool like Postman, cURL, or integrate it directly into your workflow using Python/JS scripts.","Review the response for actionable insights (e.g., quota alerts, latency issues) and adjust your workflows or provider settings accordingly."]
No install command available. Check the GitHub repository for manual installation instructions.
git clone https://github.com/zsio/claude-code-hubCopy the install command above and run it in your terminal.
Launch Claude Code, Cursor, or your preferred AI coding agent.
Use the prompt template or examples below to test the skill.
Adapt the skill to your specific use case and workflow.
Use the Claude Code Hub API to [ACTION] for [TEAM/PROJECT]. Include the following parameters: [PARAMETERS]. For example, 'Use the Claude Code Hub API to balance load across providers for the 'Q4-Analytics' project with parameters: max_retries=3, timeout=30s, and provider_priority=[anthropic, openai, mistral]'.
```json
{
"status": "success",
"request_id": "req_20241115_142233_8745",
"summary": {
"total_requests": 1250,
"balanced_distribution": {
"anthropic": 420,
"openai": 415,
"mistral": 415
},
"latency_metrics": {
"avg_response_time_ms": 185,
"p95_response_time_ms": 320,
"failed_requests": 0
},
"user_quotas": {
"user_123": {
"used": 250,
"remaining": 750,
"provider_usage": {
"anthropic": 80,
"openai": 90,
"mistral": 80
}
},
"user_456": {
"used": 180,
"remaining": 820,
"provider_usage": {
"anthropic": 60,
"openai": 60,
"mistral": 60
}
}
}
},
"recommendations": [
"Consider increasing the Mistral provider quota for user_123 as they frequently hit the limit.",
"Monitor the p95 latency for OpenAI requests; it's slightly higher than the target of 300ms.",
"Schedule a maintenance window for provider upgrades during the lowest usage period (02:00-04:00 UTC)."
]
}
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