Pricing

$5.00/month + usage

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Dataset to HuggingFace

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Developed by

AIRabbit

Transfers data from Apify datasets to Hugging Face datasets. Bridges web scraping with ML platforms, enabling access to pre-trained models and collaborative tools. Customize transfer limits, streamline ML workflows, and leverage data versioning. Ideal for data scientists and ML researchers.

0.0 (0)

Pricing

$5.00/month + usage

Total users

Monthly users

Runs succeeded

>99%

Last modified

10 months ago

Automation

Integrations

You can access the Dataset to HuggingFace programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in Integrations settings in Apify Console.

Python

JavaScript

CLI

OpenAPI

HTTP

MCP

{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/sse?actors=flamboyant_leaf/datasettohuggingface",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

Configure MCP server with Dataset to HuggingFace

You have a few options for interacting with the MCP server:

Use mcp.apify.com via mcp-remote from your local machine to connect and authenticate using OAuth or an API token (as shown in the JSON configuration above).
Set up the connection directly in your MCP client UI by providing the URL https://mcp.apify.com/sse?actors=flamboyant_leaf/datasettohuggingface along with an API token (or use OAuth).
Connect to mcp.apify.com via Server-Sent Events (SSE), as shown below:

{
    "mcpServers": {
        "apify": {
            "type": "sse",
            "url": "https://mcp.apify.com/sse?actors=flamboyant_leaf/datasettohuggingface",
            "headers": {
                "Authorization": "Bearer <YOUR_API_TOKEN>"
            }
        }
    }
}

You can connect to the Apify MCP Server using clients like Tester MCP Client, or any other MCP client of your choice.

If you want to learn more about our Apify MCP implementation, check out our MCP documentation. To learn more about the Model Context Protocol in general, refer to the official MCP documentation or read our blog post.

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