browsegrab

> Token-efficient browser agent for local LLMs — Playwright + accessibility tree + MarkGrab, MCP native.

browsegrab is a lightweight browser automation library designed for local LLMs (8B-35B parameters). It combines Playwright's accessibility tree with MarkGrab's HTML-to-markdown conversion to achieve 5-8x fewer tokens per step compared to alternatives like browser-use.

• Token-efficient: ~500-1,500 tokens/step (vs 4,000-10,000 for browser-use)
• Local LLM first: Optimized for vLLM, Ollama, and OpenAI-compatible endpoints
• MCP native: Built-in MCP server with 8 browser automation tools
• MarkGrab integration: HTML → clean markdown for content extraction
• Accessibility tree + ref system: Stable element references (e1, e2, ...) without vision models
• Success pattern caching: Zero LLM calls on repeated workflows
• 5-stage JSON parser: Robust action parsing for local LLM outputs
• Minimal dependencies: Only playwright + httpx in core

pip install browsegrab
playwright install chromium

With optional features:

pip install browsegrab[mcp]      # MCP server support
pip install browsegrab[content]  # MarkGrab content extraction
pip install browsegrab[cli]      # CLI with rich output
pip install browsegrab[all]      # Everything

from browsegrab import BrowseSession

async with BrowseSession() as session:
    # Navigate and get accessibility tree snapshot
    await session.navigate("https://example.com")
    snap = await session.snapshot()
    print(snap.tree_text)
    # - heading "Example Domain" [level=1]
    # - link "Learn more": [ref=e1]

    # Click using ref ID
    result = await session.click("e1")
    print(result.url)  # https://www.iana.org/help/example-domains

    # Type into search box
    await session.navigate("https://en.wikipedia.org")
    snap = await s