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Alternatives to OpenChrome

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    • A
      license
      B
      quality
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      maintenance
      Enables AI agents to fully control Google Chrome: navigate, click, fill forms, inspect DevTools, and manage tabs with parallel execution and session isolation.
      24
      7 npm
      MIT
    • A
      license
      B
      quality
      F
      maintenance
      Enables AI agents to directly control your real Chrome browser with full context including login sessions, cookies, and open tabs. It provides tools for page scanning, JavaScript execution, CDP control, screenshots, and physical mouse/keyboard input for authentic browser automation.
      20
      245
      MIT
    • A
      license
      C
      quality
      B
      maintenance
      Enables AI agents and developers to automate real Chrome/Chromium browsers through the Chrome DevTools Protocol, with token-efficient snapshots, multi-action batching, shadow DOM traversal, system-page control, extension management, and network/WebSocket inspection.
      64
      MIT
    • A
      license
      Not graded
      quality
      A
      maintenance
      Enables AI agents to drive a real Chrome browser for autonomous web tasks, using fast typed decisions with calibrated confidence, human-in-the-loop questions, safety gates, and full debug traces.
      959 npm
      2
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables AI assistants and terminal users to control a logged-in Chrome browser, performing actions like opening pages, searching, filling forms, and taking screenshots without re-authentication.
      MIT

    TDQS

    B3/5.0

    Scored across 122 tools

    Disambiguation2/5

    Multiple overlapping tool families create real confusion: three separate task/run systems (oc_task_*, oc_task_run_*, oc_run_*) have nearly identical start/get/list/cancel verbs, and several page-reading tools (read_page, inspect, page_content, extract_data, oc_observe) have fuzzy boundaries. Element location is split across find, query_dom, vision_find, oc_query, and oc_observe, while interact/act/computer require careful reading to distinguish. Detailed descriptions help, but the sheer number of near-duplicate surfaces will cause misselection.

    Naming Consistency2/5

    The oc_ prefixed tools follow a reasonably consistent verb_noun pattern (oc_task_run_start, oc_session_snapshot), but the legacy non-prefixed tools mix conventions wildly: some are verb_noun (read_page, fill_form), others noun_verb (page_screenshot, page_reload), and several are bare nouns (computer, network, storage, cookies, memory). The confusingly similar oc_task_run_* vs oc_task_* prefixes and odd names like javascript_tool and batch_paginate further erode consistency.

    Tool Count1/5

    122 tools is far beyond any reasonable scope for a browser automation server. There are multiple redundant subsystems (three task/run ledgers, at least five page-reading tools, three performance analyzers, two network capture tools) that inflate the surface without adding proportionate capability. This is a textbook case of tool sprawl that will overwhelm agents and add selection latency.

    Completeness4/5

    The browser automation domain is very thoroughly covered — navigation, reading, interaction, forms, network, performance, crawling, screenshots, and workflows all have extensive support with no obvious dead ends or missing core operations. If anything, completeness is over-achieved at the cost of coherence; the sprawl means completeness is high but at the expense of the other dimensions.

    Maintenance

    ActivityMaintained
    ResponsivenessWithin a week