# CrewAI

URL: https://docs.hanzo.ai/docs/guides/integrations/crewai

> LLM takes base_url. custom_openai=True is what lets you name a model id CrewAI does not recognise.

`LLM` takes **`base\_url`**. Prefix the model with `openai/\` so LiteLLM routes it through the OpenAI-compatible path.

```bash
pip install crewai
```

```python
from crewai import LLM, Agent

llm = LLM(
    model="openai/zen6",
    base_url="https://api.hanzo.ai/v1",
    api_key="sk-...",
)

agent = Agent(
    role="Researcher",
    goal="Answer precisely",
    backstory="You check before you answer.",
    llm=llm,
)
```

Lands on `POST /v1/chat/completions`.

For a model id CrewAI does not recognise as an OpenAI name, add \*\*`custom_openai=True`\*\* — that flag is what lets a gateway model id through unrewritten:

```python
llm = LLM(
    model="anthropic/claude-sonnet-4-6",
    custom_openai=True,
    base_url="https://api.hanzo.ai/v1",
    api_key="sk-...",
)
```

The environment equivalents are `OPENAI_API_KEY` and `OPENAI_BASE_URL`.

## MCP

MCP servers are first-class on the Agent, in an `mcps` list. The URL is the `url` parameter.

```python
from crewai import Agent
from crewai.mcp import MCPServerHTTP

server = MCPServerHTTP(
    url="https://api.hanzo.ai/v1/mcp",
    headers={"Authorization": "Bearer sk-..."},
    streamable=True,
    cache_tools_list=True,
)

agent = Agent(role="Researcher", goal="Answer precisely", backstory="", llm=llm, mcps=[server])
```

For manual lifecycle control there is `MCPServerAdapter` from `crewai_tools`, installed with `pip install 'crewai-tools[mcp]'`, which takes a dict of `url` and `transport`.