# strava-mcp

> Use this tool when you need to analyze personal fitness data from Strava, enabling you to query activities, segments, gear, and training trends through natural language. It solves problems related to tracking workout progress, identifying performance trends, and optimizing training routines. The tool takes natural language inputs and outputs relevant Strava activity data, making it ideal for athletes and fitness enthusiasts seeking data-driven insights.

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

## Description

Enables querying and analyzing personal Strava activity data through natural language, including activities, segments, gear, and training trends.

## Trust

- **Trust score (0–1):** 0.66
- **Verification tier:** scanned
- **Last scanned:** 2026-08-31

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-08-31

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/kma1oflwp5)
- **Repository:** <https://github.com/benniblau/strava-mcp>

## 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": "benniblau-strava-mcp"
    }
  }
}
```

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