Resources on building AI agents that browse and extract web data in real time — MCP integrations, agentic scraping patterns, and grounding LLMs with live information.
114 articles
Learn how to build an AI research agent that combines web search with AlterLab's scraping API to extract structured data from public web pages, using Python SDK and cron scheduling.
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Learn how to build a robust web search API for AI agents using RAG, headless browsers, and anti-bot handling to ensure reliable real-time data extraction.
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Explore the technical architecture of AI agents in 2026. Learn how LLMs, headless browsers, and advanced APIs enable autonomous web navigation and data extraction.
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Learn how to build agentic web browsers that handle captchas and headless detection reliably in AI workflows, with practical code examples and anti-bot strategies.
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Learn how to combine Model Context Protocol servers, agentic browsing, and AlterLab’s anti-bot handling to create low-latency, scalable RAG pipelines that fetch fresh web data on demand.
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Learn how to combine headless browsers and markdown extraction to ground LLM responses in real-time web data for reliable AI agents.
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Learn how to extract structured JSON from AlternativeTo using AlterLab's Extract API. Define a schema, call the endpoint, and get typed data ready for AI pipelines.
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Learn how to connect your AI agent to VentureBeat for real-time tech intelligence. Use AlterLab to bypass anti-bot measures and get structured JSON data.
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Extract structured SEMrush data via API using AlterLab's Extract API. Get typed JSON output for metric_name, value, date and more without HTML parsing.
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<compelling meta description, 150-160 chars, include 'ai agent' and 'bbc news'>
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Learn how to extract structured JSON from PubMed using AlterLab's data API — schema-driven, accurate, and ready for AI pipelines in 2026.
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Learn how to integrate AP News data into your AI agent pipelines using structured extraction. Use AlterLab to bypass anti-bot measures and feed clean JSON directly to your LLM.
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