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

# Run AI SDK on Blaxel

> Deploy Vercel AI SDK agent projects to Blaxel with minimal code changes to get serverless hosting, agentic observability, and governance policies.

You can deploy your [AI SDK](https://sdk.vercel.ai/docs/introduction) projects to Blaxel with minimal code editing (and zero configuration), enabling you to use [Serverless Deployments](../Infrastructure/Global-Inference-Network), [Agentic Observability](../Observability/Overview), [Policies](../Model-Governance/Policies), and more.

## Get started with AI SDK on Blaxel

To get started with AI SDK on Blaxel:

* if you already have an AI SDK agent, adapt your code with [Blaxel SDK commands](../Agents/Develop-an-agent) to connect to [MCP servers](../Functions/Overview), [LLMs](../Models/Overview) and [other agents](../Agents/Overview).
* else initialize an example project with AI SDK by using the following Blaxel CLI command and selecting the *Vercel AI hello world:*

```bash theme={null}
bl new agent
```

[Deploy](../Agents/Deploy-an-agent) it by running:

```bash theme={null}
bl deploy
```

## Develop an AI SDK agent using Blaxel features

While building your agent with AI SDK, use Blaxel [SDK](../sdk-reference/introduction) to connect to resources already hosted on Blaxel:

* [MCP servers](../Functions/Overview)
* [LLMs](../Models/Overview)
* [other agents](../Agents/Overview)

### Connect to MCP servers

Connect to [MCP servers](../Functions/Overview) using the Blaxel SDK to access pre-built or custom tool servers hosted on Blaxel. This eliminates the need to manage server connections yourself, with credentials stored securely on the platform.

Run the following command to retrieve tools in AI SDK format:

<CodeGroup>
  ```typescript TypeScript theme={null}

  import { blTools } from '@blaxel/vercel';

  const tools = await blTools(['mcp-server-name'])
  ```
</CodeGroup>

### Connect to LLMs

Connect to [LLMs](../Models/Overview) hosted on Blaxel using the SDK to avoid managing model API connections yourself. All credentials remain securely stored on the platform.

<CodeGroup>
  ```typescript TypeScript theme={null}

  import { blModel } from "@blaxel/vercel";

  const model = await blModel("model-api-name");
  ```
</CodeGroup>

### Connect to other agents

Connect to other agents hosted on Blaxel from your code by using the [Blaxel SDK](../sdk-reference/introduction). This allows for multi-agent chaining without managing connections yourself. This command is independent of the framework used to build the agent.

<CodeGroup>
  ```typescript TypeScript theme={null}

  import { blAgent } from "@blaxel/core";

  const myAgentResponse = await blAgent("agent-name").run(input);
  ```
</CodeGroup>

### Host your agent on Blaxel

You can [deploy](../Agents/Deploy-an-agent) your agent on Blaxel, enabling you to use [Serverless Deployments](../Infrastructure/Global-Inference-Network), [Agentic Observability](../Observability/Overview), [Policies](../Model-Governance/Policies), and more. This command is independent of the framework used to build the agent.

Either run the following CLI command from the root of your agent repository.

```bash theme={null}
bl deploy
```

Or [connect a GitHub repository to Blaxel](../Agents/Github-integration) for automatic deployments every time you push on *main*.