Fetcher MCP
🚀 Fetcher MCP - Playwright 无头浏览器服务器
欢迎来到 Fetcher MCP GitHub 仓库!此仓库托管了 MCP 服务器,用于使用 Playwright 无头浏览器获取网页内容。
🧠 关于
Fetcher MCP 旨在利用人工智能功能高效检索网页内容。通过利用 Playwright 无头浏览器,该服务器可以轻松浏览网页并提取所需信息。
Related MCP server: Fetch MCP
🎯 主要特点
🤖 AI 驱动的内容获取
🔗 剧作家整合
🚀 快速高效
🌟 轻松设置和配置
📚 仓库详情
名称:fetcher-mcp
描述:MCP 服务器使用 Playwright 无头浏览器获取网页内容
主题:AI、MCP、剧作家
📦最新版本
您可以从以下链接下载最新版本的 Fetcher MCP 服务器:
:information_source: 注意:
提供的链接直接指向应用程序文件。请确保下载后启动该应用程序。
如果链接无法访问或不起作用,您可以检查此存储库的“发布”部分以获取其他下载选项。
🚀 开始
要开始使用 Fetcher MCP 服务器获取内容,请按照以下简单步骤操作:
从上面的链接下载最新版本。
将下载的文件解压到您想要的位置。
启动应用程序。
根据需要配置服务器设置。
开始轻松获取网页内容!
🌐 其他资源
有关 Fetcher MCP 服务器的更多信息、资源或支持,欢迎访问官方网站https://github.com/everford/fetcher-mcp/releases 。
📝 贡献指南
我们欢迎大家为增强 Fetcher MCP 服务器的功能做出贡献,使其更加强大和高效。如果您有任何想法、建议或改进,请按照我们的指南提交拉取请求 (PR)。
🙌加入我们的社区
加入我们的社区,与其他开发人员联系,分享见解,并随时了解与 Fetcher MCP 服务器相关的最新消息:
🚀 立即开始使用 Fetcher MCP 服务器,利用 AI 驱动的功能无缝获取网页内容。使用 Playwright 无头浏览器集成,轻松提取所需信息。祝您获取愉快!🌟
请记住,Fetcher MCP 服务器简化了网页内容检索流程,使其比以往更快、更高效。立即下载最新版本,体验 AI 和 Playwright 的强大功能。祝您抓取愉快!🚀
Available Tools
2 toolsfetch_urlC
Retrieve web page content from a specified URL
| Name | Required | Description | Default |
|---|---|---|---|
| debug | No | Whether to enable debug mode (showing browser window), overrides the --debug command line flag if specified | |
| disableMedia | No | Whether to disable media resources (images, stylesheets, fonts, media), default is true | |
| extractContent | No | Whether to intelligently extract the main content, default is true | |
| maxLength | No | Maximum length of returned content (in characters), default is no limit | |
| navigationTimeout | No | Maximum time to wait for additional navigation in milliseconds, default is 10000 (10 seconds) | |
| returnHtml | No | Whether to return HTML content instead of Markdown, default is false | |
| timeout | No | Page loading timeout in milliseconds, default is 30000 (30 seconds) | |
| url | Yes | URL to fetch | |
| waitForNavigation | No | Whether to wait for additional navigation after initial page load (useful for sites with anti-bot verification), default is false | |
| waitUntil | No | Specifies when navigation is considered complete, options: 'load', 'domcontentloaded', 'networkidle', 'commit', default is 'load' |
TDQS
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 but only states the basic action. It fails to mention critical traits such as rate limits, authentication needs, potential for blocking or CAPTCHAs, error handling, or what 'retrieve' entails (e.g., using a headless browser, returning structured data). The description is too minimal for a tool with 10 parameters and complex web interactions.
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 a single, efficient sentence that front-loads the core purpose without unnecessary words. It earns its place by clearly stating what the tool does, making it highly concise and well-structured 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 complexity (10 parameters, web scraping functionality) and lack of annotations and output schema, the description is incomplete. It doesn't address behavioral aspects, error cases, or return values, leaving significant gaps for an agent to understand how to use it effectively in real-world scenarios.
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?
The description adds no parameter-specific information beyond what the input schema provides. Since schema description coverage is 100%, with detailed descriptions for all 10 parameters, the baseline score of 3 is appropriate. The description doesn't compensate but doesn't need to, as the schema fully documents parameters like 'debug', 'extractContent', and 'waitUntil'.
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 as retrieving web page content from a URL, using specific verbs ('retrieve') and resources ('web page content', 'specified URL'). It distinguishes the core function but doesn't explicitly differentiate from the sibling tool 'fetch_urls', which appears to be a plural/multiple URL version.
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 like 'fetch_urls' or other web scraping methods. It lacks context about prerequisites, limitations, or typical use cases, leaving the agent with no usage direction beyond the basic purpose.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
fetch_urlsC
Retrieve web page content from multiple specified URLs
| Name | Required | Description | Default |
|---|---|---|---|
| debug | No | Whether to enable debug mode (showing browser window), overrides the --debug command line flag if specified | |
| disableMedia | No | Whether to disable media resources (images, stylesheets, fonts, media), default is true | |
| extractContent | No | Whether to intelligently extract the main content, default is true | |
| maxLength | No | Maximum length of returned content (in characters), default is no limit | |
| navigationTimeout | No | Maximum time to wait for additional navigation in milliseconds, default is 10000 (10 seconds) | |
| returnHtml | No | Whether to return HTML content instead of Markdown, default is false | |
| timeout | No | Page loading timeout in milliseconds, default is 30000 (30 seconds) | |
| urls | Yes | Array of URLs to fetch | |
| waitForNavigation | No | Whether to wait for additional navigation after initial page load (useful for sites with anti-bot verification), default is false | |
| waitUntil | No | Specifies when navigation is considered complete, options: 'load', 'domcontentloaded', 'networkidle', 'commit', default is 'load' |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves content but lacks details on critical behaviors: it doesn't mention authentication needs, rate limits, error handling, or what the output looks like (e.g., format, structure). For a tool with 10 parameters and no output schema, this is a significant gap in transparency.
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 a single, efficient sentence: 'Retrieve web page content from multiple specified URLs.' It's front-loaded with the core purpose, has zero wasted words, and is appropriately sized for the tool's complexity. Every part of the sentence earns its place by clearly stating the action and scope.
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 complexity (10 parameters, no annotations, no output schema), the description is incomplete. It doesn't address behavioral aspects like how content is returned, error cases, or performance constraints. While the schema covers parameters well, the description fails to provide necessary context for effective use, especially without annotations or output schema to fill gaps.
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?
The schema description coverage is 100%, meaning all parameters are well-documented in the input schema itself. The description doesn't add any semantic details beyond what's in the schema (e.g., it doesn't explain how 'urls' are processed or interactions between parameters). With high schema coverage, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.
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: 'Retrieve web page content from multiple specified URLs.' It specifies the verb ('Retrieve'), resource ('web page content'), and scope ('multiple specified URLs'), which is specific and actionable. However, it doesn't explicitly distinguish this tool from its sibling 'fetch_url' (which presumably handles single URLs), missing full differentiation for a top 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 no guidance on when to use this tool versus alternatives. It doesn't mention the sibling tool 'fetch_url' or explain scenarios where fetching multiple URLs is preferred over single ones. There's no context about prerequisites, limitations, or best practices, leaving the agent without usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
2 tool updates
v1.0.0- First observed
fetch_url - First observed
fetch_urls
TDQS
Scored across 2 tools
The two tools have overlapping purposes—both fetch web page content—but the descriptions clarify that one handles a single URL while the other handles multiple URLs. This distinction is clear enough to avoid misselection, but the core functionality is identical, leading to some ambiguity in why they are separate tools.
The tool names follow a perfectly consistent verb_noun pattern with 'fetch_url' and 'fetch_urls', using snake_case throughout. The naming is predictable and clear, with no deviations in style or convention.
With only two tools, the server feels under-scoped for a general-purpose 'Fetcher' domain. A single tool with parameters for single or multiple URLs could suffice, making the current count seem redundant and inefficient for typical agent workflows.
The tool surface is severely incomplete for web fetching; it lacks essential operations like handling HTTP methods (e.g., POST), managing headers, parsing content, or error handling. Agents will face dead ends when needing more than basic retrieval, causing frequent failures.
Related MCP Connectors
Zenrows MCP server — Fetch, Extract, Batch, and Browser Sessions for AI coding assistants
Hosted browser for AI agents: screenshots, post-JS DOM, console, WCAG. No install, no API key.
Fetch and extract data from any public web page, even JS-rendered or anti-bot protected
AI-powered browser automation — navigate, click, fill forms, and extract data from any website.
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