agentmods.dev

garminconnect-mcp: Instructions file for Gemini CLI

GEMINI.md

garminconnect-mcp GEMINI.md is an instructions file for Gemini CLI from LePomas/garminconnect-mcp. It costs 625 tokens per session, scanned A, original, MIT.

Project instructions for a local MCP server that gives AI agents access to personal Garmin Connect data, such as workouts and activities. Garmin Connect is Garmin’s service for storing and viewing data from its fitness devices.

In plain words
What is it for?
Use them when setting up the project, editing its environment file, logging in to Garmin Connect, running the server, or checking its tests.
Why use it?
They explain how to install, configure, authenticate, and run the server, including the required Garmin account settings and possible multi-factor authentication.

Instructions file for Gemini CLI

Written for Gemini CLI: the file is GEMINI.md. Also seen: mentions Codex.

This is LePomas/garminconnect-mcp's own configuration. It tells Gemini CLI how to work on garminconnect-mcp itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything garminconnect-mcp configures →

not rated 0repo 2mo ago A scan 625 tokens original MIT
View source ↗ LePomas/garminconnect-mcp
Reuse

Borrowing it

Nothing to install: this file belongs to LePomas/garminconnect-mcp. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/LePomas/garminconnect-mcp/main/GEMINI.md
Clone the repo
git clone --depth 1 https://github.com/LePomas/garminconnect-mcp

Made for: Gemini CLI.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for garminconnect-mcp GEMINI.md

README.md
[![agentmods](https://agentmods.dev/badge/instructions/lepomas/garminconnect-mcp/gemini-md.svg)](https://agentmods.dev/instructions/lepomas/garminconnect-mcp/gemini-md)
Your own site
<a href="https://agentmods.dev/instructions/lepomas/garminconnect-mcp/gemini-md"><img src="https://agentmods.dev/badge/instructions/lepomas/garminconnect-mcp/gemini-md.svg" alt="Measured on agentmods" height="20"></a>
Per session 625 This file is loaded in full into every session.
When invoked 625 The same file — it is already loaded in full.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00625 $0.00625
Opus 5 $0.00313 $0.00313
Sonnet 5 $0.00125 $0.00125
Haiku 4.5 $0.00063 $0.00063

Measured 7d ago against content hash 3b86434b6761, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

garminconnect-mcp GEMINI.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

GEMINI.md · 52 lines

How it starts

The opening of the file, as written. The whole thing — 52 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Gemini Project Instructions: garminconnect-mcp

This project is a local Model Context Protocol (MCP) server that exposes Garmin Connect data to AI agents (like Codex) using the python-garminconnect library.

Project Overview

  • Purpose: Provide a secure and summarized interface to Garmin Connect personal data.
  • Technologies: Python 3.12+, mcp (FastMCP), garminconnect, python-dotenv.
  • Architecture:
    • src/garminconnect_mcp/server.py: Main entry point and tool definitions using FastMCP.
    • Uses python-garminconnect for unofficial API access.
    • Implements a caching client with MFA support.
    • Focuses on providing summarized data for workouts and activities to be more agent-friendly and privacy-conscious.

Building and Running

Setup

python3 -m venv .venv
.venv/bin/python -m pip install -e .
cp .env.example .env
# Edit .env with GARMIN_EMAIL and GARMIN_PASSWORD

Running

  • Initialize/Refresh Tokens: Run .venv/bin/garminconnect-mcp login once interactively if MFA is required or to establish tokens.
  • MCP Server: The server runs over stdio via the same command: .venv/bin/garminconnect-mcp.

Testing & Quality

  • Tests: .venv/bin/python -m pytest
  • Linting: .venv/bin/python -m ruff check .
  • Formatting: .venv/bin/python -m ruff format .
  • Privacy Scan: scripts/check-private-output.sh (Requires rg)

Development Conventions

Privacy & Data Handling

  • Crucial: Never log, print, or commit raw Garmin payloads (profile, health, activity, etc.) unless explicitly requested by the user.
  • Connectivity Checks: Use garmin_connection_status or garmin_ping for smoke tests. Avoid using garmin_profile just to check if the connection works.
  • Summarization: Prefer returning summarized, task-specific data (especially for workouts) instead of full Garmin JSON blobs.
  • Pre-commit: Always run scripts/check-private-output.sh before committing any documentation, examples, or logs to ensure no private data (like weight, birthDate, or location) is leaked.

Read the full file on GitHub · 52 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 7d ago First seen · 52 lines · 625 tokens per session scan A 3b86434b6761

Subscribe to this mod's changes

garminconnect-mcp GEMINI.md is an instructions file published in the GitHub repository LePomas/garminconnect-mcp (0 stars, last pushed 2mo ago), licensed MIT. It adds 625 tokens to every session, about $0.0031 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

claudegarmingarmin-connectmcpmodel-context-protocol
Related

Other instructions, from other repositories

codex AGENTS.md

AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.

openai/codex · 5,182 tokens

vscode buildNext.instructions.md

Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).

microsoft/vscode · 6,785 tokens

next.js AGENTS.md

AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.

vercel/next.js · 7,296 tokens

langchain AGENTS.md

AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.

langchain-ai/langchain · 4,469 tokens

vscode oss-third-party-notices.instructions.md

Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).

microsoft/vscode · 5,001 tokens

spec-kit AGENTS.md

AGENTS.md instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.

github/spec-kit · 7,104 tokens