> ## Documentation Index
> Fetch the complete documentation index at: https://docs.inference.net/llms.txt
> Use this file to discover all available pages before exploring further.

# API Keys and Authentication

> Where to find your API key, how authentication works, and security best practices.

## Managing API keys

A default API key is created for you when you create a new project. You can create additional keys or delete existing ones from the [API Keys](https://inference.net/dashboard/api-keys) page in the sidebar.

The API Keys page shows all keys across your organization and which project each one belongs to. When you click **Create API Key**, the new key is scoped to whichever project you currently have selected.

## Project scoping

API keys are scoped to a project. The key you use determines which project's resources you're interacting with — custom models, datasets, training runs, evals, and observability metrics are all grouped by the project the key belongs to.

## Permissions

When creating an API key, you can grant **read** access, **write** access, or both. For example, a read-only key for pulling metrics, or a key with write access for uploading datasets and triggering training runs.

## Authentication

Pass the key as a Bearer token in the `Authorization` header, or set it as your API key in whichever SDK you're using. The same key works across:

* **Inference API** — calling models (both off-the-shelf and custom deployments)
* **Catalyst platform** — SDK and CLI operations
* **Observability** — routing traffic through the gateway
* **MCP server** — connecting compatible AI coding assistants to Catalyst resources

## Best practices

* Keep API keys out of source control
* Rotate keys periodically
* Use environment variables to store keys in your application