Vector Database-Driven Browser Content Retrieval
Chrome MCP Server's semantic search capabilities build a complete localized text processing pipeline:
- Real-time index building: Automatically converts the contents of open tabs into vector embeddings, supports 100+ document formats
- Semantic similarity computationCosine similarity algorithm to recognize the association of concepts such as "AI technology" and "Artificial Intelligence".
- Hybrid Search Mode: Both keyword matching and natural language queries are supported, e.g., "Find the machine learning paper you read last week."
In practice, researchers can locate the target content in 50+ tabs within 3 seconds, which is a significant efficiency improvement over manual CTRL+F. The system automatically generates content summaries and timestamps, and supports jumping to the location of the original text for intensive reading.
This answer comes from the articleChrome MCP Server: the Chrome extension that lets AI control the browser for automationThe
May not be reproduced without permission:AI productivity tools " Semantic search functionality enables intelligent cross-tab retrieval through a built-in vector database
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