Readability Python MCP Server

Readability python mcp server connects Readability Python to AI assistants that speak the Model Context Protocol. This Python implementation adapts the original concept to run as python based MCP using FastMCP.

What Readability Python does

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

Key capabilities

• 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

Tools it exposes

Once connected, the assistant can call this tool directly:

• extract_content — The extract_content tool exposed by this server

Installing the readability python mcp server

Setup follows the standard MCP pattern: clone or install the server, then register it in your client's configuration file and restart the client. The configuration snippets on this page cover Claude Desktop, Claude Code and Cursor.

Where it fits

AI-service servers chain other models into your assistant, turning a single chat into a small production pipeline. Readability Python sits in that group, and the shape of its toolset — extract_content — tells you what it is really for. Worth comparing against the other ai services servers in this directory before you commit to one, since several overlap in scope but differ sharply in setup cost and permissions.

Practical notes

• This server runs locally, so it operates with whatever access your machine and its credentials already have. Scope that deliberately rather than by default.
• Maintained by jmh108, written in Python.
• MCP clients ask for confirmation before each tool call by default. Keep that on while you learn what the readability python mcp server actually does with your data.
• Every entry in this directory is reviewed by hand before it goes live, and details are checked against the project's own documentation.