原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
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Thinkrun

作者:dundas版本 0.3.14i★ –i在你的电脑上运行
注册名称io.github.dundas/thinkrun

安装

概览

作者提供的说明(英文原文)

Browser control + session recording MCP for AI coding agents (Claude Code, Cursor) — real Chrome.

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

  • 连接方式: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 网页与浏览器

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
  • 注册中心没有列出需要填写的密钥。

你需要

  • npm已安装 Node.js(用于 npx 命令)

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "thinkrun": {
      "command": "npx",
      "args": [
        "-y",
        "@thinkrun/mcp"
      ]
    }
  }
}

在终端中运行这条命令

claude mcp add thinkrun -- npx -y @thinkrun/mcp

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "thinkrun": {
      "command": "npx",
      "args": [
        "-y",
        "@thinkrun/mcp"
      ]
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "thinkrun": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@thinkrun/mcp"
      ]
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上,无需账户。

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

它能做什么

它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月6日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 dundas 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    它在你的电脑上运行;我们只能读取互联网端点的工具列表

与“网页与浏览器”中的其他服务器比较i

  • 星标数多于此分类中其他 875 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 875 个服务器的 92% 更新
  • 基础检查结果等于或优于此分类中其他 875 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

Thinkrun 安全吗?

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。

它在我的电脑上运行还是在云端?

它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(0.3.14)于3天前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Node.js。

有什么可以替代它?

同一分类中有:Browser Use, Chrome DevTools MCP, MCP Server Browser

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Browser Use

作者:browser-use

Browser agents and stealth cloud browsers for AI: run web tasks, fill forms, extract data.

电脑或云端★ 120,087MIT16天前更新
安装

Chrome DevTools MCP

作者:ChromeDevTools

MCP server for Chrome DevTools

在你的电脑上运行★ 54,821Apache-2.015天前更新
安装

MCP Server Browser

作者:bytedance

MCP server for browser use access

在你的电脑上运行★ 39,550Apache-2.014个月前更新
安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

ThinkRun — Screen Recorder for AI Coding Agents

Stop screenshotting bugs and typing paragraphs to explain them. ThinkRun records any browser session — or lets your agent record what it built — and turns it into structured context your AI coding agent can act on: every click, the console, network requests, your voice narration, and screenshots, all time-synced. Not just a screenshot. Not just a video.

Works with Claude Code, Cursor, Cline, Windsurf, and any MCP client.

Install

npx @thinkrun/mcp

Or install the CLI globally:

npm install -g @thinkrun/cli

The CLI automatically installs the native host binary, which lets AI tools control Chrome.

Add to your MCP config

{

"mcpServers": { "thinkrun": { "command": "npx", "args": ["@thinkrun/mcp"] } } }

Config location:

  • Claude Code: ~/.claude/settings.json
  • Cursor: .cursor/mcp.json
  • Cline: VS Code settings → Cline MCP Servers

Then ask your agent: *"navigate to localhost:3000 and screenshot the checkout page"* — or record the bug yourself and hand the agent the result.

Why ThinkRun

Other tools give your agent eyes. ThinkRun gives it structured sight — context it can parse in one pass instead of you re-explaining the page.

ThinkRunPlaywright MCP
Records a session into structured, replayable context✅❌ drive-only
Turns a recording into an AI-ready report (clicks, console, network)✅❌
Shareable link, also as LLM-ready Markdown / JSON✅❌
Uses your real Chrome — your cookies & sessions✅❌ headless only
Runs alongside your browser, no profile conflict✅❌ fights for Chrome profile

Agent skills for Claude Code, Cursor, Codex & Gemini CLI

Six portable agent skills ship in this repo, mirrored for every major harness (.claude/skills/, .cursor/skills/, .codex/skills/, .gemini/skills/):

  • prove-it — the prove step of a software-factory workflow: named test targets in, a pass/fail table with a screenshot, console and network capture per target out, posted to the PR; any non-pass row sends the change back to build.
  • before-after — the ship step: two captures at the same viewport, one | Before | After | table for the PR, no public paste host.
  • web-browse — browse the web programmatically: drive a real or cloud browser to navigate, interact, extract, and screenshot.
  • ux-audit — walk through a product UI as a real user, screenshot every step, and produce a structured UX report with a prioritized fix list.
  • thinkbrowse-cli — drive the browser from shell scripts via the thinkrun CLI.
  • thinkbrowse-mcp — drive the browser through the ThinkRun MCP server's tools.

Install without cloning — the repo is served as a live MCP server that auto-updates on every commit:

{ "mcpServers": { "thinkrun-skills": { "url": "https://mcp.skillsovermcp.com/mcp/dundas/thinkrun" } } }

Trigger accuracy is measured, not claimed. Every skill ships a 20-query trigger-eval fixture, and evals/BENCHMARK.md publishes the results: with the six-skill catalog (v4, 2026-09-18), 120/120 on GPT-5.6-terra and Claude Fable 5 and 113/120 on Claude Sonnet 5 (its documented strict-MCP reading, not a crash); the earlier four-skill matrix scored 79–80/80 on 12 of 16 model configurations. Catalog-ablation runs show the browsing skills absorb each other's traffic when installed as a subset, and that prove-it fills a gap rather than duplicating a sibling (before-after folds into prove-it when absent). Reproduce with bun evals/run-eval.ts build.

Manual binary install

If you need to install the native host without the CLI, download the binary for your platform from the latest release and run:

chmod +x thinkbrowse-host-* && ./thinkbrowse-host-* --install

The native host binary keeps the thinkbrowse-host filename for now — it's the same signed binary, unchanged by the rename.

FAQ

How do I give Claude Code (or Cursor) access to my browser?

Add ThinkRun as an MCP server — npx @thinkrun/mcp — and your agent can drive and read a real Chrome session, your cookies and logins included. See "Add to your MCP config" above.

How do I show Cursor a UI bug instead of pasting a screenshot?

Record the bug with ThinkRun. Instead of a flat image, your agent gets a structured artifact — the steps you took, the console errors, the failing network requests, and the DOM state at the moment it broke — so it fixes the actual problem instead of guessing from a picture.

Is there an MCP server that uses my real Chrome cookies and sessions?

Yes. ThinkRun runs against your real Chrome via a native host, so authenticated pages just work — no headless re-login, no separate profile, no fighting your browser for the Chrome profile.

How do I record a browser session for an AI coding agent?

Run npx @thinkrun/mcp (or npm i -g @thinkrun/cli) and record any session — or let the agent record what it built. ThinkRun turns it into an AI-ready report (clicks, console, network, narration, screenshots, all time-synced), available as a shareable link and as LLM-ready Markdown/JSON.

How do I give my AI coding agent context about what went wrong?

Hand it a ThinkRun recording. The structured "what happened" — actions, first bad signal, expected vs actual, and the element state — is exactly the context an agent needs to land a fix on the first try.

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