> For the complete documentation index, see [llms.txt](https://doc.thordata.com/doc/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://doc.thordata.com/doc/scraping/serp-api/integration/sdk-integration/how-to-set-up-thordata-with-langchain.md).

# How to Set Up ThorData with LangChain

Set up Thordata with LangChain to fetch real-time SERP data and use structured search results inside AI applications.

Integrate ThorData with LangChain to provide LLM-based agents with reliable, anonymous, and scalable web access for executing real-world data tasks, covering 190 countries and regions.

You can use the `langchain-thordata` Python package to implement this integration, which supports the following features:

* ThorSerpTool – ThorData offers a powerful SERP API that allows you to query search engines (Google, Bing, Yandex, DuckDuckGo) using geolocation and advanced customization options—features particularly useful for AI agents requiring real-time web information.

Alternatively, via ThorData's MCP (Model Context Protocol)—a local server providing various scraping and automation tools — Although it is not part of the `langchain-thordata` package, it can be manually integrated using LangChain's `Tool` or `RequestsWrapper`.

#### How to integrate ThorData with LangChain

{% stepper %}
{% step %}
**Get your ThorData API Token**

* Log in to your [ThorData dashboard](https://dashboard.thordata.com/serp-api/get-started).
* Go to [SERP API > API Token](https://dashboard.thordata.com/serp-api/get-started). If you haven't generated an API token yet, please generate one.
  {% endstep %}

{% step %}
**Install the ThorData integration**

Run the following command to install the ThorData integration package for LangChain:

```
pip install langchain-thordata
```

{% endstep %}

{% step %}
**Set environment variables**

Set your ThorData API Token as an environment variable:

```
import os
os.environ["THOR_API_KEY"] = "your-token"
```

{% endstep %}

{% step %}
**Using the ThorData + LangChain integration**

API Reference: SERP API Documentation

Basic Usage

```
from langchain_thordata import ThorSerpTool

search_tool = ThorSerpTool.from_env()

result = search_tool.invoke({
    "query": "LangChain tutorial",
    "engine": "google",
    "params": {
        "gl": "us",
        "hl": "en",
        "device": "desktop",
    },
})

print(result)
```

{% endstep %}

{% step %}
**Use within an Agent**

```
from langchain_thordata import ThorSerpTool
from langchain_openai import ChatOpenAI

llm = ChatOpenAI(model="gpt-4o-mini", temperature=0)
tool = ThorSerpTool.from_env()

# Tool calling without langchain_classic agents
model_with_tools = llm.bind_tools([tool])
response = model_with_tools.invoke("Search for the latest LangChain news")
print(response)
```

{% endstep %}
{% endstepper %}