MCP 工具，用于使用 Chrome 浏览器进行 Google 搜索和网页内容提取。与 Claude 配合使用，可实现 Google 搜索和内容抓取功能。
配置 Claude 桌面
在 Mac 上打开 Claude Desktop
前往 Claude > 设置 > 开发者 > 编辑配置
将以下内容添加到您的配置文件中：GXP1
重启Claude桌面
首次设置
授予无障碍权限
首次运行时，批准 macOS 辅助功能权限提示
导航至：系统偏好设置 > 安全和隐私 > 隐私 > 辅助功能
为您的终端应用添加并启用权限
从 Apple 事件启用 Chrome JavaScript
打开 Chrome
导航至：查看 > 开发者 > 允许来自 Apple 事件的 JavaScript
仅需一次性设置
配置完成后，当您发出请求时，Claude 将能够执行 Google 搜索并通过 Chrome 提取网页内容。
Related MCP server: Google Search MCP
免费搜索谷歌
打开小窗口并使用 Chrome 浏览器，因此不会被阻止
由于它正在使用你的 Chrome 窗口，因此可以访问经过身份验证的内容。Claude 只需在你的浏览器中打开 URL 即可。
✅ macOS
❌ Windows（不支持）
❌ Linux（不支持）
macOS
谷歌浏览器
Node.js 20 或更高版本
npx mcp-chrome-google-search从 git 签出
运行npm run build
添加到 Claude 配置（使用绝对路径）：
{
"google-tools": {
"command": "node",
"args": [
"/your/checkout/path/mcp/mcp-chrome-google-search/dist/index.js"
]
}
}要在本地测试更改，请提高 package.json 版本并运行以将其置于编辑模式：
npm install -g .然后只需执行npm run build ，文件就会进入 claude 正在监控的 dist 中
然后在 Claude 桌面按 ctrl-R，无需重新启动
# Follow logs in real-time
tail -n 20 -F ~/Library/Logs/Claude/mcp*.log启用开发者设置：
echo '{"allowDevTools": true}' > ~/Library/Application\ Support/Claude/developer_settings.json打开 DevTools：在 Claude 桌面中打开 Command-Option-Shift-i
在 Claude 桌面中使用 ctrl-r 来获取更好的错误信息
如果你看到：
execution error: Google Chrome got an error: Executing JavaScript through AppleScript
is turned off. For more information: https://support.google.com/chrome/?p=applescript (12)解决方案：
打开 Chrome
查看 > 开发者 > 允许来自 Apple 事件的 JavaScript
如果 Chrome 控制失败：
打开系统偏好设置
安全和隐私 > 隐私 > 可访问性
确保终端应用程序已列出并启用
如果需要，使用锁定图标进行更改
使用 AppleScript 控制 Chrome
可见的自动化 - Chrome 窗口将打开/导航
每个请求都会打开一个新的 Chrome 标签页
定期关闭未使用的标签以获得最佳性能
仅与受信任的 Claude 实例一起使用（具有 Chrome 控制访问权限）
为问题创建 GitHub 问题
包含 macOS 和 Chrome 版本详细信息
MIT 许可证 - 详情请参阅许可证文件
Extract readable text content from a webpage using Chrome browser automation.
Key Features:
Returns main content text and optionally links
| Name | Required | Description | Default |
|---|---|---|---|
| includeLinks | No | Whether to include extracted links in the output | |
| url | Yes | Webpage URL to fetch (must include http:// or https://) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions Chrome browser automation and returning main content text with optional links, but lacks critical behavioral details: it doesn't specify if this is a read-only operation, potential rate limits, authentication needs, error handling for inaccessible pages, or what 'readable text' entails (e.g., stripping HTML, handling dynamic content). The description adds some context but leaves significant gaps for a tool interacting with external webpages.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured with a clear opening sentence followed by a bullet point. Every sentence earns its place by stating the core purpose and a key feature. However, the bullet point format is slightly redundant with the main sentence, and it could be more front-loaded by integrating the optional links feature into the initial statement.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of web scraping (external interactions, potential failures) and lack of annotations or output schema, the description is incomplete. It doesn't explain return values beyond 'main content text and optionally links', leaving the agent uncertain about output structure, error responses, or behavioral constraints like timeouts or permissions. For a tool with no structured safety hints, this is inadequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with clear descriptions for both parameters in the schema itself. The description adds minimal value beyond the schema: it mentions 'optionally links' which aligns with the 'includeLinks' parameter but doesn't provide additional semantic context. With high schema coverage, the baseline is 3, and the description doesn't significantly enhance parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Extract readable text content from a webpage using Chrome browser automation.' It specifies the verb (extract), resource (text content from a webpage), and method (Chrome browser automation). However, it doesn't explicitly differentiate from its sibling 'web-search' tool, which likely searches rather than extracts content from a specific URL.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It mentions 'optionally links' as a feature but doesn't clarify scenarios where including links is beneficial or when to choose this over 'web-search'. There's no mention of prerequisites, limitations, or typical use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Search webpages and get a specific page of results (each page has ~10 results). Optionally filter by site and timeframe.
| Name | Required | Description | Default |
|---|---|---|---|
| pageNumber | No | Which page of results to fetch (1-5). Each page contains ~10 results | |
| query_text | Yes | Plain text to search for (no Google operators plain text only - use other parameters for site/date filtering) | |
| site | No | Limit search to specific domain (e.g. 'github.com' or 'docs.python.org') | |
| timeframe | No | Time range filter (h=hour, d=day, w=week, m=month, y=year) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It adds some context beyond basic functionality: it mentions pagination ('each page has ~10 results') and optional filtering capabilities. However, it doesn't cover important aspects like rate limits, authentication needs, error handling, or what the output looks like (e.g., result format), which are significant gaps for a search tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise and front-loaded: it states the core purpose in the first clause and adds key details in a second sentence. Every word earns its place, with no redundancy or fluff, making it highly efficient for quick understanding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (4 parameters, no output schema, no annotations), the description is somewhat complete but has gaps. It covers the basic operation and filtering options but lacks details on output format, error cases, or integration with the sibling tool. Without annotations or output schema, more behavioral context would be beneficial for full completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds minimal value beyond the schema by hinting at the optional nature of site and timeframe filters, but it doesn't provide additional semantic context or usage examples. This meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Search webpages and get a specific page of results.' It specifies the verb ('search') and resource ('webpages'), and distinguishes it from the sibling tool 'web_fetch' by implying this is for search results rather than fetching specific pages. However, it doesn't explicitly contrast with the sibling, keeping it from a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides implied usage context by mentioning optional filters ('Optionally filter by site and timeframe'), which suggests when to use these parameters. However, it lacks explicit guidance on when to choose this tool over the sibling 'web_fetch' or any other alternatives, and doesn't specify prerequisites or exclusions, leaving room for ambiguity.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
v1.0.0web_fetchweb-searchScored across 2 tools
The two tools have clearly distinct purposes: web_fetch extracts content from a specific webpage, while web_search performs web searches and returns result pages. There is no overlap in functionality, making it easy for an agent to choose the correct tool based on the task.
Both tool names follow a consistent snake_case pattern with a clear verb-noun structure: web_fetch and web_search. The naming is predictable and readable, with no deviations in style or convention.
With only 2 tools, the server feels thin for a Google Search domain, which typically involves more operations like advanced filtering, image search, or history management. While the tools cover basic fetch and search, the scope is limited and could benefit from additional functionality to fully represent the domain.
The tools cover core search and content extraction, but there are notable gaps for a Google Search server, such as no tools for image search, news search, or handling search settings. Agents can perform basic tasks but may encounter dead ends for more advanced operations, indicating incomplete coverage of the domain.
Google search, news, maps, scholar and public webpages for AI agents, with Markdown results.
Real Chrome for agents: start a browser, read pages as numbered markdown, click, type, hand off.
Web search, browser automation, scraping, crawling and CAPTCHA solving for AI agents.
Web search and page-reading for AI agents. One-click OAuth connect, or a Caesar API key.
