Agentic Browser cuts LLM web agent token use by up to 98% over raw HTML

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A developer has released Agentic Browser, an open-source Python browser built on Playwright and Chromium, designed to help large language models navigate the web far more efficiently than traditional scrapers. Instead of feeding models raw HTML that can exceed 100,000 tokens, the tool provides compact structured observations using roles, labels, and element references. Benchmarks show token reductions of up to 99.4% on pages like the GTA VI landing site and 98.3% on GitHub repositories. The tool supports the Model Context Protocol and is compatible with OpenAI and Anthropic tool schemas, making it plug-in ready for hosts like Cursor and Claude Desktop. Available under the MIT license for Python 3.11 and above, version 0.4.0 has been published on GitHub with 118 automated tests included.

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