Retrieves user geolocation information for integration with large language models via the Model Context Protocol.
Sponsored
This project serves as a practical demonstration of integrating user geolocation data with large language models through the Model Context Protocol (MCP). It leverages EdgeOne Pages Functions to accurately retrieve a user's location, which is then exposed as a callable tool for AI models via an MCP server. This setup enables AI applications to become location-aware, enhancing their ability to provide contextually relevant responses and services.
Key Features
01Retrieves user geolocation using EdgeOne Pages Functions
02Integrates geolocation data with Large Language Models via MCP
03Exposes a 'get_geolocation' tool for AI models
04Returns location information in JSON format
05Uses EdgeOne request context for geolocation access
060 GitHub stars
Use Cases
01Demonstrate integration of EdgeOne Pages Functions with external services for AI models
02Provide real-time location context to large language models
03Develop AI applications requiring user-specific geographical information
