Do I have to manually format scraped data for AI workflows?

Learn about the automated data formatting options available in Web Scraper API and AI Studio for AI workflows.

Web Scraper API

Only if you want to. Model Context Protocol (MCP) standardizes scraped data in LLM-ready format.

🛠️ MCP is a built-in feature of Web Scraper API 🛠️

Configurable parameters allow you to tailor Web Scraper API outputs to specific AI model requirements with minimal setup changes.

Key benefits of MCP

• Consistency: ensure reliable input to AI systems with standardized formatting.

• Scalability: easily handle large-scale web scraping for LLMs.

• Cost efficiency: reduce engineering costs for maintaining data pipelines.

See our documentation and GitHub for specific steps to enable MCP for your projects.

You can also use a Markdown output feature. This provides a clean, structured data of web content that is highly optimized and easy-to-read for LLMs. To enable it, include the "markdown": true parameter in your request.

AI Studio

AI Studio delivers results in LLM-optimized Markdown format. If needed, it can automatically parse results based on your specifications: define your needs through natural language prompts or provide Pydantic/JSON schemas.