# Strava

> Use this tool when you need to integrate fitness tracking data and activity information into AI-powered health and wellness applications, analyzing workout patterns and tracking athletic performance. It provides access to Strava's extensive fitness ecosystem through the Model Context Protocol SDK and FastAPI. Ideal for use cases requiring detailed fitness data analysis and integration, such as developing personalized workout recommendations or health monitoring systems.

Canonical page: https://skillsregistry.net/skills/ctvidic-strava  
JSON: https://api.skillsregistry.net/v1/skills/ctvidic-strava

## Description

This MCP server implementation provides integration with the Strava API, enabling access to fitness tracking data and activity information. Developed by Christopher Vidic, it utilizes FastAPI and the Model Context Protocol SDK to offer a bridge between AI assistants and Strava's extensive fitness ecosystem. The server is designed for use cases such as analyzing workout patterns, tracking athletic performance, and integrating fitness data into AI-powered health and wellness applications.

## Trust

- **Trust score (0–1):** 0.86
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** api-integration
- **Updated:** 2026-09-19

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/ctvidic-strava)
- **Repository:** <https://github.com/ctvidic/strava-mcp-server>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "ctvidic-strava"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/ctvidic-strava` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/ctvidic-strava/pull`

---
SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt