OpenRouter is an API layer for using many AI models through one account, one API key, and one OpenAI-compatible API endpoint. Instead of connecting every app to a different model provider, an app can send requests to OpenRouter and choose a model by its model slug.
This is useful for tools that support bring-your-own-key access. You keep your own OpenRouter account, choose the model you want, pay for your own usage, and paste the key into a trusted app only when the app needs to call an AI model.
What an OpenRouter API key does
An OpenRouter API key is a private credential. It tells OpenRouter which account should pay for the request and what limits or permissions should apply. Treat it like a password for AI model usage.
When an app asks for an OpenRouter API key, the app normally uses it to call the OpenRouter API, send your prompt to the selected model, and return the model answer. The app should not publish your key, log it, or send it anywhere except the API provider.
How to use an OpenRouter API key
1. Create or sign in to your OpenRouter account.
2. Open the API keys area in your OpenRouter settings.
3. Create a new key with a clear name, for example English Trainer or Personal Tests.
4. Set a spending limit if the account screen offers one.
5. Copy the key once and keep it private.
6. Paste it into the AI tool that asks for an OpenRouter key.
7. Choose a model, run a small test, and check usage in your OpenRouter account.
Safety checklist
Do not paste an OpenRouter API key into random websites, public code, screenshots, chat messages, or GitHub repositories. If a key is exposed, create a new key, update your tools, and revoke the old key.
For browser-only tools, understand the tradeoff: if a tool runs entirely in your browser, the key may be stored locally on your device. That can be convenient, but you should use trusted pages only, keep browser extensions under control, and use a low spending limit for testing.
When OpenRouter is a good fit
OpenRouter is a good fit when you want model choice, quick experimentation, and one API shape for many LLMs. It is especially handy for learning projects, AI writing tools, coding helpers, English practice apps, and prototypes where you want to switch models without rewriting the whole app.