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MCP Server Readability Parser: Code Clarity & Ghost-Free Code - MCP Implementation

MCP Server Readability Parser: Code Clarity & Ghost-Free Code

MCP Server’s Clarity Mirror: Shatters readability roadblocks with Python/FastMCP – no more cryptic code ghosts! 🖥️✨

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Ranked in the top 6% of all AI tools in its category

About MCP Server Readability Parser

What is MCP Server Readability Parser: Code Clarity & Ghost-Free Code?

This Python-based MCP server leverages the Mozilla Readability algorithm to clean and structure webpage content into LLM-friendly Markdown. Built using FastMCP, it strips away clutter like ads and navigation elements while preserving core content. The solution optimizes text for AI processing and reduces token waste through smart HTML parsing and conversion.

How to Use MCP Server Readability Parser: Code Clarity & Ghost-Free Code?

Setup Steps

  1. Clone repository: git clone https://github.com/jmh108/MCP-server-readability-python
  2. Create virtual environment and install dependencies
  3. Launch server with fastmcp run server.py

API Usage Example

curl -X POST http://localhost:8000/tools/extract_content \
-H "Content-Type: application/json" \
-d '{"url": "https://example.com"}'
    

MCP Server Readability Parser Features

Key Features of MCP Server Readability Parser: Code Clarity & Ghost-Free Code?

  • Ad/nonsense filtering using proven Readability logic
  • Automated HTML-to-Markdown conversion with semantic structure
  • Error handling for broken or dynamic web content
  • Lightweight MCP integration for scalable deployments
  • Supports modern web content including JavaScript-rendered pages

Use Cases for MCP Server Readability Parser

Content Processing Pipelines

Automate article cleanup for AI training datasets

Chatbot Integration

Preprocess user-provided URLs into consumable text formats

Data Scraping

Extract clean text from web sources while avoiding legal noise

Token Optimization

Reduce API costs by removing redundant page elements

MCP Server Readability Parser FAQ

FAQ: Code Clarity & Ghost-Free Code

Do I need GPU resources?

No, runs efficiently on standard CPU configurations

How does it handle dynamic content?

Uses headless browser emulation for JavaScript-rendered pages

Can I customize cleanup rules?

Yes, configuration options allow element whitelisting/blacklisting

What licenses apply?

MIT License for core code, dependencies follow their own terms

Content

MCP Server Readability Parser (Python / FastMCP)

Credits/Reference

This project is based on the original server-moz-readability implementation of emzimmer. (For the original README documentation, please refer to the original README.md.)

This Python implementation adapts the original concept to run as python based MCP using FastMCP

Mozilla Readability Parser MCP Server

A Python implementation of the Model Context Protocol (MCP) server that extracts and transforms webpage content into clean, LLM-optimized Markdown.

Table of Contents

  • Features
  • Why Not Just Fetch?
  • Installation
  • Quick Start
  • Tool Reference
  • Dependencies
  • License

Features

  • Removes ads, navigation, footers and other non-essential content
  • Converts clean HTML into well-formatted Markdown
  • Handles errors gracefully
  • Optimized for LLM processing
  • Lightweight and fast

Why Not Just Fetch?

Unlike simple fetch requests, this server:

  • Extracts only relevant content using Readability algorithm
  • Eliminates noise like ads, popups, and navigation menus
  • Reduces token usage by removing unnecessary HTML/CSS
  • Provides consistent Markdown formatting for better LLM processing
  • Handles complex web pages with dynamic content

Installation

  1. Clone the repository:
git clone https://github.com/jmh108/MCP-server-readability-python.git
cd MCP-server-readability-python
  1. Create and activate a virtual environment:
python -m venv venv
source venv/bin/activate  # On Windows use: venv\Scripts\activate
  1. Install dependencies:
pip install -r requirements.txt

Quick Start

  1. Start the server:
fastmcp run server.py
  1. Example request:
curl -X POST http://localhost:8000/tools/extract_content \
  -H "Content-Type: application/json" \
  -d '{"url": "https://example.com/article"}'

Tool Reference

extract_content

Fetches and transforms webpage content into clean Markdown.

Arguments:

{
  "url": {
    "type": "string",
    "description": "The website URL to parse",
    "required": true
  }
}

Returns:

{
  "content": "Markdown content..."
}

MCP Server Configuration

To configure the MCP server, add the following to your MCP settings file:

{
  "mcpServers": {
    "readability": {
      "command": "fastmcp",
      "args": ["run", "server.py"],
      "env": {}
    }
  }
}

The server can then be started using the MCP protocol and accessed via the parse tool.

Dependencies

License

MIT License - See LICENSE for details.

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