Agentic Browser: ~98% fewer tokens than HTML for LLM web agents (Python + MCP)

Agentic Browser is an agent-first Python browser built on Playwright/Chromium so LLMs can drive the web with compact observations, stable element refs, and outcome-verified actions ? not raw HTML dumps. Why it exists Traditional scrapers hand models 100k+ tokens of markup. Agents need: Small structured observations (roles, labels, refs) Actions that mean success (URL/DOM outcomes) A plug-in for any host (MCP + OpenAI/Anthropic tool schemas) Measured token efficiency Scenario Raw HTML Compact observation Reduction Quotes scrape ~2.8k?6.2k ~0.45k?1.3k ~78?84% Rockstar GTA VI landing ~225,000 ~1,300 ~99.4% GitHub vercel/next.js ~110,000 ~1,900 ~98.3% Features Stable refs + scoped grounding Outcome verification (e.g. Issues click only OK if URL is /issues) Page gates for challenges (detect & report ? not a bypass tool) MCP server for Cursor / Claude Desktop tools_as_openai() / tools_as_anthropic() 118 automated tests; milestones M1?M10 Install pip install agent-browser playwright install chromium agent-browser --help # MCP python -m agent_browser.mcp Enter fullscreen mode Exit fullscreen mode Links GitHub: https://github.com/applejuice093/Agentic-browser Release: https://github.com/applejuice093/Agentic-browser/releases/tag/v0.4.0 MIT ? Python 3.11+