> For the complete documentation index, see [llms.txt](https://docs.alkemi.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.alkemi.ai/documentation/getting-started.md).

# Getting Started

- [Quickstart](https://docs.alkemi.ai/documentation/getting-started/quickstart.md): Get an overview of the DataLab interface and ask your first questions to the agent.
- [Connect Alkemi to Claude](https://docs.alkemi.ai/documentation/getting-started/connect-alkemi-to-claude.md): Securely querying Alkemi data from Claude is easy thanks to Alkemi's OAuth MCP features.
- [Connect Alkemi to ChatGPT](https://docs.alkemi.ai/documentation/getting-started/connect-alkemi-to-chatgpt.md): Securely querying Alkemi data from ChatGPT is easy thanks to Alkemi's OAuth MCP features.
- [Searching and Scraping the Web](https://docs.alkemi.ai/documentation/getting-started/searching-and-scraping-the-web.md): Alkemi DataLab comes with tools that enable you to easily search the web and scrape content.
- [Searching the Web](https://docs.alkemi.ai/documentation/getting-started/searching-and-scraping-the-web/searching-the-web.md): Alkemi's web search tool enables you to search for terms and pull in the results to DataLab
- [Scraping a Website](https://docs.alkemi.ai/documentation/getting-started/searching-and-scraping-the-web/scraping-a-website.md): Alkemi's web scrape tool enables you to scrape content from a URL pull in the results to DataLab
- [Researching a Company](https://docs.alkemi.ai/documentation/getting-started/searching-and-scraping-the-web/researching-a-company.md): Alkemi's company research tool enables you to research information and news about a company and pull in the results to DataLab
- [Connect your data](https://docs.alkemi.ai/documentation/getting-started/connect-your-data.md)
- [Uploading Files](https://docs.alkemi.ai/documentation/getting-started/connect-your-data/uploading-files.md)
- [Transforming a CSV](https://docs.alkemi.ai/documentation/getting-started/connect-your-data/uploading-files/transforming-a-csv.md): Transforming an uploaded CSV into a new data asset within DataLab is easy. Simply ask the AI agent to transform the data and you can create a completely new data asset tailored to your needs.
- [Exporting to CSV](https://docs.alkemi.ai/documentation/getting-started/connect-your-data/uploading-files/exporting-to-csv.md): Exporting to CSV in DataLab is simple.
- [Connecting Databricks](https://docs.alkemi.ai/documentation/getting-started/connect-your-data/connecting-databricks.md): Connect your Databricks workspace to the Alkemi platform. Once connected, you can create and manage Data Products within Alkemi using your Databricks warehouse as the data source.
- [Connecting Snowflake](https://docs.alkemi.ai/documentation/getting-started/connect-your-data/connecting-snowflake.md): Connect your Snowflake workspace to the Alkemi platform. Once connected, you can create and manage Data Products within Alkemi using your Snowflake database as the data source.
- [Connecting BigQuery](https://docs.alkemi.ai/documentation/getting-started/connect-your-data/connecting-bigquery.md): Learn how to connect your Google BigQuery Dataset to the Alkemi platform. Once connected, you can create and manage Data Products within Alkemi using your Google BigQuery Dataset as the data source.
- [Connecting Linear](https://docs.alkemi.ai/documentation/getting-started/connect-your-data/connecting-linear.md): See how to securely connect your Linear workspace to Alkemi and get insights into your issues and product status
- [Querying your data](https://docs.alkemi.ai/documentation/getting-started/querying-your-data.md)


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# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.alkemi.ai/documentation/getting-started.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.