F
licenseNot graded
qualityD
maintenanceFetches web pages and converts them to clean, readable markdown format by extracting main content while removing navigation, ads, and other non-essential elements to minimize token usage.
4
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Mozilla Readability Parser MCP Server
by emzimmer
Mozilla Readability 解析器 MCP 服务器
一个模型上下文协议 (MCP)服务器，用于提取网页内容并将其转换为干净的、LLM 优化的 Markdown 格式。返回文章标题、正文、摘录、署名和网站名称。使用Mozilla 的 Readability 算法移除广告、导航、页脚和不必要的元素，同时保留核心内容结构。了解更多关于 MCP 的信息。
特征
删除广告、导航、页脚和其他非必要内容
将干净的 HTML 转换为格式良好的 Markdown（也使用 Turndown）
返回文章元数据（标题、摘录、署名、网站名称）
优雅地处理错误
Related MCP server: cleanfetch
为什么不直接获取？
与简单的获取请求不同，此服务器：
使用 Mozilla 的可读性算法仅提取相关内容
消除广告、弹出窗口和导航菜单等噪音
通过删除不必要的 HTML/CSS 来减少令牌的使用
提供一致的 Markdown 格式，以便更好地处理 LLM
包含有关内容的有用元数据
安装
通过 Smithery 安装
要通过Smithery自动为 Claude Desktop 安装 Mozilla Readability Parser：
npx -y @smithery/cli install server-moz-readability --client claude手动安装
npm install server-moz-readability工具参考
parse
获取网页内容并将其转换为干净的 Markdown。
参数：
{
"url": {
"type": "string",
"description": "The website URL to parse",
"required": true
}
}返回：
{
"title": "Article title",
"content": "Markdown content...",
"metadata": {
"excerpt": "Brief summary",
"byline": "Author information",
"siteName": "Source website name"
}
}与 Claude Desktop 一起使用
添加到您的claude_desktop_config.json ：
{
"mcpServers": {
"readability": {
"command": "npx",
"args": ["-y", "server-moz-readability"]
}
}
}依赖项
@mozilla/readability——内容提取
turndown - HTML 到 Markdown 的转换
jsdom——DOM 解析
axios - HTTP 请求
执照
麻省理工学院
Available Tools
1 toolparseA
Extracts and transforms webpage content into clean, LLM-optimized Markdown. Returns article title, main content, excerpt, byline and site name. Uses Mozilla's Readability algorithm to remove ads, navigation, footers and non-essential elements while preserving the core content structure.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | The website URL to parse |
TDQS
A4/5.0
Behavior4/5
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 effectively describes key behaviors: the transformation process ('extracts and transforms'), the algorithm used ('Mozilla's Readability algorithm'), what gets removed ('ads, navigation, footers and non-essential elements'), and what is preserved ('core content structure'). However, it doesn't mention potential limitations like rate limits, authentication needs, or error conditions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded, with two sentences that efficiently convey the tool's purpose, output, and key behavioral traits. Every sentence adds value without redundancy, making it easy to understand at a glance.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (single parameter, no output schema, no annotations), the description is largely complete. It explains what the tool does, how it processes content, and what it returns. However, without an output schema, it could benefit from more detail on the return structure (e.g., format of the Markdown), and it lacks information on error handling or edge cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, with the parameter 'url' clearly documented as 'The website URL to parse'. The description doesn't add any additional meaning or context about the parameter beyond what the schema provides, such as URL format requirements or examples. With high schema coverage, the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with specific verbs ('extracts and transforms') and resources ('webpage content'), specifying the output format ('clean, LLM-optimized Markdown') and what it returns ('article title, main content, excerpt, byline and site name'). It distinguishes itself by mentioning the algorithm used ('Mozilla's Readability algorithm') and what it removes ('ads, navigation, footers and non-essential elements').
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for extracting structured content from webpages, but does not explicitly state when to use this tool versus alternatives, nor provide exclusions or prerequisites. With no sibling tools, the lack of explicit guidelines is less critical, but it still doesn't offer clear when/when-not instructions.
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.
1 tool update
v1.0.0- First observed
parse
TDQS
A3.9/5.0
Scored across 1 tool
Disambiguation5/5
With only one tool, there is no possibility of ambiguity or overlap between tools. The single tool has a clear and distinct purpose focused on parsing webpage content into clean Markdown.
Naming Consistency5/5
A single tool inherently has perfect naming consistency, as there are no other tools to compare against. The tool name 'parse' is straightforward and appropriate for its function.
Tool Count2/5
A single tool is too few for a server's purpose, even if that purpose is narrow. This limits functionality and makes the server feel thin, as it lacks complementary operations like configuration, validation, or batch processing that might be expected in a parsing domain.
Completeness2/5
The tool surface is severely incomplete for a parsing server. While the 'parse' tool covers the core extraction function, there are obvious gaps such as no tools for handling errors, validating inputs, managing configurations, or providing metadata about the parsing process, which could lead to agent failures in real-world scenarios.
Maintenance
ActivityInactive
ResponsivenessUnresponsive
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Related MCP Servers
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