copilot-api

🥈Silver

Copilot API exposes GitHub Copilot through an OpenAI and Anthropic-compatible API, enabling direct usage with Claude Code. Operations teams can integrate AI-powered code suggestions into their workflows, improving developer productivity and code quality. Connects to GitHub Copilot, Claude Code, and other AI models.

6410Updated 1mo ago

Intermediate30min to implementautomation

Saves ~60 min per use

Quick InstallView Source

git clone https://github.com/prassaaa/copilot-api.git

Works with:

Claude

Overview

About This Skill

Copilot API is a reverse-engineered proxy server that exposes GitHub Copilot through OpenAI and Anthropic API formats, enabling integration with Claude Code and other compatible tools. It provides a mobile-first dashboard for managing multiple GitHub accounts, monitoring token quota usage across Chat, Completions, and Premium tiers, and testing endpoints via an integrated API playground. The server supports automatic account rotation using four strategies (sticky, round-robin, quota-based, hybrid), real-time request logging with Server-Sent Events, and model fallback capabilities. Developers and operations teams can use it to integrate AI-powered code suggestions directly into their workflows without needing proprietary Copilot integrations. Built with Bun, it runs locally and requires only a GitHub account with Copilot access.

How to Use

1. **Set Up Copilot API Access**: Ensure you have access to the Copilot API and a valid API key. Configure your environment to use the API with your preferred tool (e.g., Claude Code, Postman). 2. **Define Requirements**: Clearly specify the programming language, functionality, and any standards (e.g., security, performance) in your prompt. Use placeholders like [LANGUAGE] and [DESCRIBE_FUNCTIONALITY]. 3. **Generate Code**: Paste the prompt into your AI tool (e.g., Claude Code) and execute it. Review the generated code for accuracy and completeness. 4. **Integrate and Test**: Copy the generated code into your project. Test it thoroughly, especially edge cases and error handling. Use tools like `pytest` (Python) or `Jest` (JavaScript) for validation. 5. **Iterate**: If the output isn’t perfect, refine your prompt with more specific requirements (e.g., "Use async/await for I/O operations" or "Follow SOLID principles"). **Tip**: For complex projects, break the task into smaller chunks (e.g., generate a function first, then the API endpoint). Use the Copilot API’s context window to provide additional files or documentation for better results.

Use Cases

Integrate GitHub Copilot with Claude Code without an Anthropic API key

Route Copilot requests through tools requiring OpenAI-compatible APIs

Monitor and manage Copilot quota usage across multiple GitHub accounts

Test Copilot API endpoints with the built-in playground before production use

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/prassaaa/copilot-api

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

Use the Copilot API to generate [LANGUAGE] code for [DESCRIBE_FUNCTIONALITY]. Ensure the code follows best practices for [SPECIFIC_STANDARD, e.g., performance, readability, security]. Include comments explaining key sections. Output the code in a single code block. Example: 'Use the Copilot API to generate Python code for a REST API endpoint that processes user authentication tokens. Follow PEP 8 guidelines and include JWT validation.'

Example Output

```python
import jwt
from flask import Flask, request, jsonify
from datetime import datetime, timedelta

app = Flask(__name__)

# Secret key for JWT token signing (in production, use environment variables)
SECRET_KEY = 'your-secret-key-here'

@app.route('/authenticate', methods=['POST'])
def authenticate():
    """
    Authenticate a user and return a JWT token.
    Expects JSON payload: {'username': 'user', 'password': 'pass'}
    """
    data = request.get_json()
    username = data.get('username')
    password = data.get('password')

    # Validate credentials (in production, use a database or auth service)
    if username != 'admin' or password != 'securepassword123':
        return jsonify({'error': 'Invalid credentials'}), 401

    # Generate JWT token with 1-hour expiration
    token = jwt.encode({
        'username': username,
        'exp': datetime.utcnow() + timedelta(hours=1)
    }, SECRET_KEY, algorithm='HS256')

    return jsonify({'token': token}), 200

if __name__ == '__main__':
    app.run(debug=True)
```

### Key Features:
- **JWT Validation**: Uses PyJWT for secure token handling.
- **Error Handling**: Returns 401 for invalid credentials.
- **Expiration**: Tokens expire after 1 hour for security.
- **Flask Integration**: Follows REST API conventions.

### Next Steps:
1. Replace `SECRET_KEY` with an environment variable in production.
2. Add rate limiting to prevent brute-force attacks.
3. Integrate with a user database for real authentication.