> For the complete documentation index, see [llms.txt](https://v2.dataos.info/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://v2.dataos.info/consume/v1/consume-with-ai/connect-an-agentic-framework/agentscope.md).

# AgentScope

Connect Data Product MCP to an AgentScope application with the `HttpStatelessClient`, so your agent works from governed products instead of guessing.

## Prerequisites

Python 3.9 or later, your DataOS instance URL, and a [DataOS API token](/consume/v1/get-started/before-you-begin.md).

## Connect

1. Install AgentScope with the `service` extra:

```bash
pip install agentscope[service]
```

2. Register the MCP client, replacing the placeholders:

```python
import asyncio
from agentscope.mcp import HttpStatelessClient
from agentscope.tool import Toolkit

client = HttpStatelessClient(
    name="DataProduct-MCP",
    transport="streamable_http",
    url="https://<instance-url>/dataproduct-mcp/api/v1",
    headers={"apikey": "<API_TOKEN>"},
)

async def main():
    toolkit = Toolkit()
    await toolkit.register_mcp_client(client)
    print(f"Loaded {len(toolkit.get_json_schemas())} tools from DataOS MCP")

asyncio.run(main())
```

The `toolkit` holds the registered Data Product MCP tools and their schemas. Pass it to your AgentScope agents as you would any other toolkit.

{% hint style="warning" %}
[API tokens](https://v2.dataos.info/references/key-concepts/api-tokens) are secrets. Pass the token through an environment variable rather than hardcoding it.
{% endhint %}

## Verify

Run the script and confirm the toolkit loads Data Product MCP tools. Then ask the agent `What data products am I authorized to access?`. A working connection returns products scoped to your token.


---

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