mcp-garmin-connect

mcp-garmin-connect

An MCP server that gives LLMs access to Garmin Connect data, including training, recovery, sleep, stress, VO2 Max, and running summaries for personalized fitness advice.

Category
Visit Server

README

mcp-garmin-connect

Python 3.11+ MCP License: MIT CI Top Language

LLM-agnostic Garmin Connect MCP server for training, recovery, sleep, stress, VO2 Max, race predictions, and running summaries.

Use the same local Garmin tools from MCP clients such as Claude Desktop, Claude Code, Cursor, Continue, Hermes, or from provider-backed demo agents using DeepSeek, OpenAI, or Claude API.

Why This Exists

Most fitness advice from LLMs is generic. This server lets an LLM inspect your real Garmin Connect data first, then answer with context from your activities, recovery markers, HRV, sleep, stress, VO2 Max, and running history.

The core server is provider-neutral. DeepSeek, OpenAI, and Claude integrations are optional demo bridges for clients that do not speak MCP directly.

Features

  • Local MCP server for Garmin Connect over stdio or Streamable HTTP.
  • 14 Garmin tools and 4 prompt templates.
  • Provider demo bridge for deepseek, openai, claude, openrouter, and gemini.
  • Windows-first CLI, with cross-platform Python project structure.
  • Explicit opt-in before Garmin health/activity data is sent to any external LLM provider.
  • Mocked test suite plus optional live Garmin smoke tests.

Languages And Stack

Area Technology
Main language Python 3.11+
Package manager uv
MCP server mcp Python SDK / FastMCP
Garmin access garminconnect
Provider API calls httpx
Tests pytest
Linting ruff
Client config examples JSON, YAML, PowerShell

Quick Start

uv sync
Copy-Item .env.example .env
notepad .env

Set Garmin credentials:

GARMIN_EMAIL=you@example.com
GARMIN_PASSWORD=your-password

Authenticate once:

uv run garmin-mcp login
uv run garmin-mcp doctor --live

List available MCP tools:

uv run garmin-mcp tools

Run as a local MCP server:

uv run garmin-mcp serve --transport stdio

Run as an HTTP MCP server:

uv run garmin-mcp serve --transport http --host 127.0.0.1 --port 8765

HTTP clients can connect to:

http://127.0.0.1:8765/mcp

Provider Demo Agents

Provider API access may require a paid account or credits even if the provider's web app has a free tier.

DEEPSEEK_API_KEY=sk-...
OPENAI_API_KEY=sk-...
ANTHROPIC_API_KEY=sk-ant-...
OPENROUTER_API_KEY=sk-or-...
GEMINI_API_KEY=...
Provider Env key Default model API style
DeepSeek DEEPSEEK_API_KEY deepseek-v4-pro OpenAI-compatible Chat Completions
OpenAI OPENAI_API_KEY gpt-5 OpenAI Chat Completions
Claude ANTHROPIC_API_KEY claude-sonnet-5 Anthropic Messages API
OpenRouter OPENROUTER_API_KEY google/gemini-3-flash-preview OpenAI-compatible Chat Completions
Gemini GEMINI_API_KEY gemini-3.6-flash Gemini Generate Content API

Ask through a provider bridge:

uv run garmin-mcp ask "How is my recovery today?" --provider deepseek --allow-external-health-data
uv run garmin-mcp ask "Summarize my running for 90 days." --provider openai --allow-external-health-data
uv run garmin-mcp ask "What should I focus on this week?" --provider claude --allow-external-health-data
uv run garmin-mcp ask "Summarize my monthly running." --provider openrouter --allow-external-health-data
uv run garmin-mcp ask "Check my fitness trend." --provider gemini --allow-external-health-data

The --allow-external-health-data flag is required because Garmin tool results can be sent to the selected provider.

MCP Tools

Tool Purpose
get_recovery Readiness, HRV, sleep, body battery, resting HR, training status if available
get_sleep Sleep duration and sleep score trends
get_stress Daily stress buckets and average stress
get_recent_activities Recent normalized activity summaries
get_activity_detail One activity with training effect fields
get_recent_load Volume by sport based on recent activities
get_training_load Native Garmin Training Load when the device/account exposes it
get_fitness VO2 Max, FTP, and race predictions
get_zones Heart-rate and power zones when available
get_personal_records Garmin personal records
get_running_summary 90-day running summary with pace, HR, longest and fastest run
get_monthly_running_stats Monthly running breakdown
get_health_summary Compact recovery, sleep, and stress snapshot
get_full_snapshot Broad multi-section Garmin snapshot

MCP Prompts

  • recovery_check
  • weekly_training_review
  • activity_analysis
  • race_plan_context

Client Setup

See docs/clients for examples covering:

  • Claude Desktop
  • Claude Code
  • Cursor
  • Continue
  • Hermes
  • Generic stdio MCP clients
  • Generic HTTP MCP clients

Minimal stdio config:

{
  "mcpServers": {
    "garmin": {
      "command": "uv",
      "args": [
        "--directory",
        "C:\\path\\to\\mcp-garmin-connect",
        "run",
        "garmin-mcp",
        "serve",
        "--transport",
        "stdio"
      ]
    }
  }
}

Testing

uv run garmin-mcp doctor
uv run garmin-mcp doctor --live
uv run garmin-mcp tools
uv run ruff check .
uv run pytest

Optional live tests are gated and do not run in CI by default:

$env:GARMIN_LIVE_TEST = "1"
uv run pytest tests/live

Current local validation target:

ruff: All checks passed
pytest: all mocked tests pass, live test skipped unless enabled

Privacy And Safety

Your .env file and Garmin token cache stay local and are ignored by git.

MCP clients that run locally can call Garmin tools without sending provider API keys to this project. Provider demo commands such as garmin-mcp ask can send Garmin health/activity results to the selected LLM provider, so the CLI requires --allow-external-health-data.

Garmin Disclaimer

This project uses the community garminconnect Python package and Garmin Connect endpoints. Garmin Connect is not a public API for individual open-source projects, and authentication or endpoint behavior may change without notice.

Some metrics depend on Garmin device capabilities. For example, a device may expose VO2 Max and Training Effect but not native Garmin Training Load or Training Status.

Star History

<a href="https://www.star-history.com/?repos=kavakoss%2Fmcp-garmin-connect&type=date&legend=top-left"> <picture> <source media="(prefers-color-scheme: dark)" srcset="https://api.star-history.com/chart?repos=kavakoss/mcp-garmin-connect&type=date&theme=dark&legend=top-left&sealed_token=jWwCP1aKpJ82FKqcEEP2UnyXxxIF8WVj4b0NmJGkZDR5Iujd8WmJ43JHjxO4epA5RTFxdG-30WvZcDNhA31RsI3lKr8R1056ExLsKXwknwg1YhFvCGqR1PffqsTOp-s8HNBovtGPGdPAQIbXZEe0YHGaNj3JZ2eWrOBHcBgwa6MVkqHgHzkSMc6EM4En" /> <source media="(prefers-color-scheme: light)" srcset="https://api.star-history.com/chart?repos=kavakoss/mcp-garmin-connect&type=date&legend=top-left&sealed_token=jWwCP1aKpJ82FKqcEEP2UnyXxxIF8WVj4b0NmJGkZDR5Iujd8WmJ43JHjxO4epA5RTFxdG-30WvZcDNhA31RsI3lKr8R1056ExLsKXwknwg1YhFvCGqR1PffqsTOp-s8HNBovtGPGdPAQIbXZEe0YHGaNj3JZ2eWrOBHcBgwa6MVkqHgHzkSMc6EM4En" /> <img alt="Star History Chart" src="https://api.star-history.com/chart?repos=kavakoss/mcp-garmin-connect&type=date&legend=top-left&sealed_token=jWwCP1aKpJ82FKqcEEP2UnyXxxIF8WVj4b0NmJGkZDR5Iujd8WmJ43JHjxO4epA5RTFxdG-30WvZcDNhA31RsI3lKr8R1056ExLsKXwknwg1YhFvCGqR1PffqsTOp-s8HNBovtGPGdPAQIbXZEe0YHGaNj3JZ2eWrOBHcBgwa6MVkqHgHzkSMc6EM4En" /> </picture> </a>

License

This project is licensed under the MIT License.

Publish

Codex does not push this repo. To publish it yourself:

git remote add origin https://github.com/kavakoss/mcp-garmin-connect.git
git push -u origin main

Made by kavakoss.

Inspired by Jack-Abyss/claude-garmin, with a clean-room implementation focused on LLM-agnostic MCP usage.

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured