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How I Built Smart Scraper M2M: A Fast ~30ms Scraper API for AI Agents

A developer built Smart Scraper M2M, a lightweight web scraper API designed for machine-to-machine communication, achieving response times of approximately 30 milliseconds. The tool aims to address the bottleneck of heavy, slow web scraping in AI agent frameworks like CrewAI and LangChain, reducing context bloat and LLM token costs. The source code is available on GitHub.

read1 min views1 publishedAug 23, 2026

Building AI Agents with frameworks like CrewAI or LangChain often hits a bottleneck: heavy, slow web scraping that bloats context windows and increases LLM token costs.

To solve this, I built Smart Scraper M2M — a lightweight, high-performance web scraper API designed specifically for machine-to-machine (M2M) communication.

~30ms

.You can test the API or check the full source code directly on GitHub:

🔗 GitHub Repository: https://github.com/MRIGL/smart-scraper-m2m I’m actively improving the API and would love to hear your thoughts, feature requests, or contributions! Feel free to star the repo or leave a comment below.

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