This MCP implementation, developed using TypeScript, provides a robust foundation for building and deploying web scraping and automation projects. It leverages the Apify platform and Crawlee library, offering a structured environment for creating scalable web crawlers and data extraction tasks. The implementation includes configuration files for ESLint, TypeScript, and Docker, ensuring code quality and consistency across different development environments. By abstracting common web scraping challenges and providing integration with Apify's cloud infrastructure, this tool enables developers to focus on building complex data acquisition workflows. It is particularly useful for projects requiring large-scale web data extraction, automated testing of web applications, or building AI training datasets from web sources.
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Retrieves documentation, input schema, and details about a specific Actor.
Searches for relevant Actors using keywords and returns their details.
Adds an Actor by name to the available tools list without executing it, requiring user consent to run later.
Removes an Actor by name from the available tools list when it's no longer needed.
