> ## 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 CrewAI on Blaxel

> Deploy multi-agent CrewAI systems on Blaxel with serverless hosting, observability, and connections to MCP servers and LLM APIs.

[CrewAI](https://www.crewai.com/) is a framework for orchestrating autonomous AI agents — enabling you to create AI teams where each agent has specific roles, tools, and goals, working together to accomplish complex tasks. You can deploy your CrewAI 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 CrewAI on Blaxel

To get started with CrewAI on Blaxel:

* if you already have a CrewAI 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 in CrewAI by using the following Blaxel CLI command and selecting the *CrewAI hello world:*

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

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

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

## Develop a CrewAI agent using Blaxel features

While building your agent in CrewAI, 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 CrewAI format:

<CodeGroup>
  ```python Python theme={null}

  from blaxel.crewai import bl_tools

  await bl_tools(['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>
  ```python Python theme={null}

  from blaxel.crewai import bl_model

  model = await bl_model("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>
  ```python Python theme={null}

  from blaxel.core.agents import bl_agent

  response = await bl_agent("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*.