> For clean Markdown of any page, append .md to the page URL.
> For a complete documentation index, see https://docs.fabricgateway.ai/llms.txt.
> For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.fabricgateway.ai/_mcp/server.

# Get started with Fabric Gateway

> Connect your first LLM provider or MCP server, and send a test request through the gateway.

> **Info**
>
> This topic describes the product direction and implementation, but much of the platform is still evolving. Some details, capabilities, and decisions may change as development continues.

This topic walks you through connecting your first LLM provider or MCP server and sending a test request through the gateway.

## Prerequisites

Before you begin, make sure you have the following:

* Access to a Fabric AI Gateway organization, with permission to create connections.
* An API key or token from the provider you want to connect.
* Postman, if you want to send the test request from a Postman collection.

## Connect a provider

You can connect an LLM provider or an MCP server. This topic uses an LLM provider. To connect an MCP server, see [Connect an MCP server](/fabric/gateways/mcp-servers).

To connect a provider, do the following:

1. In the sidebar, select **LLMs** (or **MCP servers**), and then select the **Providers** tab.
2. Find your provider, and then select **Connect**.
3. Follow the setup wizard. When it finishes, you have a connection that holds your provider credential and a route that your clients can call. The wizard also creates a gateway key for the route.

Have the following ready before you start:

* Your provider API key.
* The models that you want to expose through the route.

For a description of the connection settings, see [Connect an LLM provider](/fabric/gateways/llm-providers).

## Send a test request from Postman

Before you point an application at the gateway, test the route to confirm that it works. To send a request to an OpenAI route from Postman, do the following:

1. In the sidebar, select **LLMs** > **Routes**, find your OpenAI route, and then select **Copy LLM base URL**.

2. In Postman, create a request with the method `POST`. For the URL, paste the base URL that you copied, followed by `/v1/chat/completions`.

3. In the **Headers** tab, add `fg-api-key` with your gateway key as the value. For more information, see [Authenticate requests with Key Auth](/fabric/plugins/key-auth).

4. In the **Body** tab, select **raw** and **JSON**, and then enter the following body:

   ```json
   {
     "model": "gpt-4o-mini",
     "messages": [
       { "role": "user", "content": "Hello from Fabric Gateway!" }
     ]
   }
   ```

5. Select **Send**.

The request doesn't include your provider's API key, because the gateway adds the key that you saved on the connection.

> **Note**
>
> If you run your own data plane, the copied URL has no host until an admin sets one in **Admin** > **Data plane**.

The response is a standard OpenAI chat completion (`200 OK`) with the model name and the assistant's reply. It confirms that the gateway proxies the request to the upstream provider while it enforces the gateway key.

If the request returns `401 Unauthorized`, see the troubleshooting steps in the Key Auth topic.

## Next steps

* Learn the platform model in [Fabric AI Gateway architecture](/get-started/architecture) before you expand your deployment.
* To add authentication, rate limiting, routing, or transforms to a route, see [Control traffic with plugins](/fabric/plugins).
* To observe traffic through the gateway, see [Monitor gateway traffic](/fabric/observability).
* To give your team access, see [Administer your organization](/fabric/administration).