How I Built Smart Scraper M2M: A Fast ~30ms Scraper API for AI Agents
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. 🌟 Key Features ⚡ Ultra-fast: Returns clean structured JSON in ~30ms . 🧠…
Smart Scraper M2M is a fast and efficient web scraper API designed specifically for machine-to-machine communication, enabling AI agents to process relevant data quickly. The API, built by a developer, offers several key features:
1. Ultra-fast performance: It returns clean structured JSON data in a remarkable 30ms.
2. Context-optimization: By stripping out unnecessary HTML and CSS elements, the API ensures LLMs only process relevant information.
3. Agent-friendliness: Smart Scraper M2M is designed to integrate seamlessly with popular frameworks like CrewAI, LangChain, and custom Node.js agents.
To use the API, developers can quickly test it or explore the full source code on GitHub. The repository is live at https://github.com/MRIGL/smart-scraper-m2m. The developer is actively working on improving the API and encourages feedback, feature requests, or contributions. To get involved, users can star the repository or leave a comment on the project page.
Written by urgent.news from Dev.to's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
