Strava Python

Strava Python extends your AI assistant with the ability to query Strava activities, stats, and workout data using Python/stravalib with interactive setup. Rather than leaving your conversation to handle this manually, you can ask your Claude agent directly — and it will take care of the task end-to-end, using Strava Python as its underlying capability.

Strava Python works across Claude, Cursor, OpenClaw through the Model Context Protocol (MCP) — an open standard that lets AI clients share tools and skills without lock-in. Because MCP is platform-agnostic by design, you install Strava Python once and it becomes available across all your AI clients. Whether you're working in Claude for focused sessions or Cursor for integrated workflows, the skill behaves consistently.

Getting started with Strava Python takes about two minutes. Place the skill at `~/.claude/skills/strava-python/` (personal, all projects) or `.claude/skills/strava-python/` (project-specific), then restart your AI client. From that point, typing `/strava-python` in any conversation activates it, or the AI will use it on its own when it detects a relevant request.

Strava Python has been installed 1,048 times, making it one of the more actively used skills in the Developer & DevOps category. The install rate suggests it solves a real, recurring need rather than a niche edge case. The source code is open on GitHub — you can inspect it, contribute fixes, or fork it to adapt the skill for your specific setup. Like all skills on DiscoverAISkills, it is free to install and use. The broader AI skills ecosystem continues to expand as developers contribute new capabilities across categories like developer tools, data analysis, writing, automation, and more.