Documentation

LLM Documentation

We've created a comprehensive LLM documentation file that contains all the information about CurrencyAPI in a format optimized for AI assistants and Large Language Models (LLMs).

You can access the complete documentation at https://currencyapi.net/llms.txt

This documentation file allows AI assistants like ChatGPT, Claude, Cursor, Windsurf, and others to quickly understand our API capabilities and help you integrate CurrencyAPI more efficiently.

What our LLM Documentation contains?

The file is designed to be easily consumed by AI assistants, providing them with all the context they need to help you work with our API effectively.

  • Complete product overview and features
  • All API endpoints with examples and parameters
  • Full list of 152 supported currencies
  • Pricing plans and technical specifications
  • SDK information and popular pages
  • Company information and support details

How to Use

To use our LLM documentation with your preferred AI assistant:

  • Copy the URL: Use https://currencyapi.net/llms.txt
  • Paste in your LLM: Share the URL with your AI assistant
  • Ask questions: The LLM will have full context about our API
  • Get code examples: Request specific implementation examples
  • Plan integrations: Ask for architecture recommendations

Supported LLMs

Our LLM documentation works with all major AI assistants and development tools:

  • ChatGPT: Paste the URL in your conversation
  • Claude (Anthropic): Share the link for context
  • Cursor: Use the URL in your AI chat
  • Windsurf: Reference the documentation file
  • GitHub Copilot: Include the URL in your prompts
  • Amazon CodeWhisperer: Reference the documentation
  • Tabnine: Use the URL for enhanced suggestions
  • Any other LLM: Most AI assistants can access and process the file

Best Practices

To get the most out of our LLM documentation:

  • Be specific: Ask for specific endpoints or features you need
  • Request code examples: Ask for implementation in your preferred language
  • Ask for best practices: Get recommendations for error handling and optimization
  • Request architecture advice: Ask for integration patterns and recommendations
  • Test the suggestions: Always test code examples before using in production
  • Stay updated: The documentation is updated regularly with new features

The LLM documentation is automatically updated whenever we add new features or endpoints, ensuring your AI assistant always has the latest information about our API.