MCP Internet Speed Test
An implementation of a Model Context Protocol (MCP) for internet speed testing. It allows AI models and agents to measure, analyze, and report network performance metrics through a standardized interface.
📦 Available on PyPI: https://pypi.org/project/mcp-internet-speed-test/
🚀 Quick Start:
pip install mcp-internet-speed-test
mcp-internet-speed-testWhat is MCP?
The Model Context Protocol (MCP) provides a standardized way for Large Language Models (LLMs) to interact with external tools and data sources. Think of it as the "USB-C for AI applications" - a common interface that allows AI systems to access real-world capabilities and information.
Features
- Smart Incremental Testing: Uses SpeedOf.Me methodology with 8-second threshold for optimal accuracy
- Download Speed Testing: Measures bandwidth using files from 128KB to 128MB from GitHub repository (Git LFS)
- Upload Speed Testing: Tests upload bandwidth using streaming data from 128KB to 128MB
- Latency Testing: Measures network latency using multiple samples, reports minimum value
- Jitter Analysis: Calculates network stability using multiple latency samples (default: 5)
- Multi-CDN Support: Detects and provides info for Fastly, Cloudflare, and AWS CloudFront
- Geographic Location: Maps POP codes to physical locations (50+ locations worldwide)
- Cache Analysis: Detects HIT/MISS status and cache headers
- Server Metadata: Extracts detailed CDN headers including
x-served-by,via,x-cache - Comprehensive Testing: Single function to run all tests with complete metrics
