Pricing

Pay per usage

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/llms.txt Generator

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Developed by

Jakub Kopecký

The /llms.txt Generator 🕸️📄 extracts website content to create an llms.txt file for AI apps 🤖✨ like LLM fine-tuning and indexing. Output is available 📥 in the Key-Value Store for easy download and integration into workflows. 🚀

2.7 (2)

Pricing

Pay per usage

Total users

348

Monthly users

128

Runs succeeded

88%

Issues response

1.1 hours

Last modified

a month ago

Automation

Open source

You can access the /llms.txt Generator 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=jakub.kopecky/llmstxt-generator",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

Configure MCP server with /llms.txt Generator

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=jakub.kopecky/llmstxt-generator 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=jakub.kopecky/llmstxt-generator",
            "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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