Mozilla Readability Parser MCP Server
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Alternatives to Mozilla Readability Parser MCP Server
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Related Servers
- AlicenseAqualityBmaintenanceConverts any URL to clean, LLM-ready Markdown by removing ads, navigation, and other clutter, using Mozilla Readability and Turndown.119 npmMIT
- FlicenseNot gradedqualityCmaintenanceFetches webpages and returns clean, structured Markdown with metadata (title, author, publish date, description, domain, word count).-
- AlicenseNot gradedqualityDmaintenanceConverts any webpage into clean, LLM-ready Markdown, removing noise and supporting JavaScript rendering.MIT
- AlicenseNot gradedqualityDmaintenanceConverts URLs into clean, LLM-ready markdown, respecting robots.txt and never bypassing anti-bot measures or paywalls.MIT
- AlicenseAqualityCmaintenanceEnables AI agents to read web pages reliably, returning clean markdown content, hyperlinks, and metadata without navigation or ad noise.36 npmMIT
- FlicenseNot gradedqualityDmaintenanceFetches 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-
TDQS
Scored across 1 tool
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.
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.
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.
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.