> 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/langchain.md).

# LangChain

Connecting Data Product MCP to a LangChain agent lets it answer from governed products instead of guessing. The `langchain-mcp-adapters` package registers DataOS tools so your agent works with trusted, authorized data. See the [LangChain MCP documentation](https://docs.langchain.com/oss/python/langchain/mcp) for adapter setup and transports.

## 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 the adapter:

```bash
pip install langchain-mcp-adapters
```

2. Following the LangChain MCP docs, initialize an MCP client over HTTP transport with these DataOS values:

| Parameter    | Value                                           |
| ------------ | ----------------------------------------------- |
| Transport    | `http`                                          |
| URL          | `https://<instance-url>/dataproduct-mcp/api/v1` |
| Header key   | `apikey`                                        |
| Header value | Your DataOS API token                           |

{% 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 `get_tools()` returns 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.


---

# Agent Instructions
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## Querying This Documentation
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Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://v2.dataos.info/consume/v1/consume-with-ai/connect-an-agentic-framework/langchain.md?ask=<question>&goal=<endgoal>
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