anyclaude

🥈Silver

Use Claude Code with OpenAI, Google, xAI, and other providers. Simple setup with a basic command wrapper. Supports C and integrates with AI SDK for easy provider support.

256320Updated Today

Intermediate30min to implementautomation

Saves ~180 min per use

Quick InstallView Source

git clone https://github.com/coder/anyclaude.git

Works with:

Claude

Overview

About This Skill

Use Claude Code with OpenAI, Google, xAI, and other providers. Simple setup with a basic command wrapper. Supports C and integrates with AI SDK for easy provider support.

Setup & Installation

Quick Install

No install command available. Check the GitHub repository for manual installation instructions.

Alternative Install (Git Clone)

git clone https://github.com/coder/anyclaude

Requirements

Claude Code or compatible AI agent
Works with: Claude

Quick Start Guide

Install the Skill

Copy the install command above and run it in your terminal.

Open Your AI Agent

Launch Claude Code, Cursor, or your preferred AI coding agent.

Try It Out

Use the prompt template or examples below to test the skill.

Customize

Adapt the skill to your specific use case and workflow.

Usage Examples

Prompt Template

I want to use Claude Code to interact with [OTHER_LLM] to perform [TASK]. Here's the prompt I want to send: '[PROMPT]'. Please generate the Python code to make this happen.

Example Output

```python
# Claude Code Integration with ChatGPT

import requests
import json

# Define the API endpoints and headers
claude_endpoint = 'https://api.anthropic.com/v1/messages'
chatgpt_endpoint = 'https://api.openai.com/v1/chat/completions'

headers_claude = {
    'Content-Type': 'application/json',
    'Authorization': 'Bearer YOUR_CLAUDE_API_KEY'
}

headers_chatgpt = {
    'Content-Type': 'application/json',
    'Authorization': 'Bearer YOUR_CHATGPT_API_KEY'
}

# Define the prompt to be sent to ChatGPT
prompt = {
    'model': 'gpt-3.5-turbo',
    'messages': [
        {'role': 'user', 'content': 'Explain the concept of quantum computing in simple terms.'}
    ]
}

# Send the prompt to ChatGPT
response = requests.post(chatgpt_endpoint, headers=headers_chatgpt, json=prompt)
response_data = response.json()

# Extract the response from ChatGPT
chatgpt_response = response_data['choices'][0]['message']['content']

# Send the ChatGPT response to Claude for further processing
claude_prompt = {
    'model': 'claude-2',
    'messages': [
        {'role': 'user', 'content': f'Here is the response from ChatGPT: {chatgpt_response}. Analyze it and provide a summary.'}
    ]
}

# Send the prompt to Claude
claude_response = requests.post(claude_endpoint, headers=headers_claude, json=claude_prompt)
claude_response_data = claude_response.json()

# Extract the response from Claude
claude_summary = claude_response_data['choices'][0]['message']['content']

print('ChatGPT Response:', chatgpt_response)
print('Claude Summary:', claude_summary)
```