Technical Implementation of Intelligent Page Analysis
OpenDia's page analytics functionality relies on the following technology stack:
- MCP protocol layer: Establish a persistent WebSocket connection between the browser extension and the local server for low-latency bi-directional communication
- Content Extraction Engine: Fetch structured web content via DOM parsing algorithms, including:
- Using APIs like querySelector to locate body regions
- Apply Readability class algorithms to filter noisy content such as advertisements
- AI integration interface: Transfer of extracted content to connected AI models (e.g. Claude/ChatGPT) via standardized JSON format
Example of a typical workflow:
User inputs "summary page" command → extension triggers content capture → sends to local LLM via MCP protocol → AI generates summary → results are returned and displayed in extension UI. The whole process is usually completed within 2-3 seconds.
This answer comes from the articleOpenDia: An Open Source Tool to Connect Browsers to AI ModelsThe
May not be reproduced without permission:AI productivity tools " What is the technical principle behind OpenDia's implementation of Page Intelligence Analytics?
English 
简体中文 
日本語 
Deutsch 
Português do Brasil