# Garmin MCP Lite

> Use this tool when you need to access and query Garmin Connect data for endurance athletes, enabling natural-language queries of activity, training, health, device, and goal information through 12 curated endpoints. It solves problems related to data retrieval and analysis for athletes, providing a lightweight and efficient way to retrieve relevant information. Ideal for use cases where athletes or coaches need to quickly access and understand performance data, the Garmin MCP Lite server accepts natural-language queries as input and returns relevant data as output.

Canonical page: https://skillsregistry.net/skills/golden0voyager-garmin-mcp-lite  
JSON: https://api.skillsregistry.net/v1/skills/golden0voyager-garmin-mcp-lite

## Description

A lightweight Garmin Model Context Protocol server with 12 curated endpoints for endurance athletes, enabling natural-language queries of activity, training, health, device, and goal data from Garmin Connect.

## Trust

- **Trust score (0–1):** 0.99
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

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

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/qr8rzuao0x)
- **Repository:** <https://github.com/Golden0Voyager/garmin-mcp-lite>

## 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": "golden0voyager-garmin-mcp-lite"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/golden0voyager-garmin-mcp-lite` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/golden0voyager-garmin-mcp-lite/pull`

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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