What is garmin-grafana-mcp-server copilot-instructions.md?

Project instructions for a Python MCP server that reads Garmin health and training data from a local InfluxDB database for AI clients.

Use them when working on data queries, MCP tools, FastAPI endpoints, health checks, or shared helpers. The server provides data but does not interpret it or give coaching advice.

They explain the server's architecture, database measurements, connection boundaries, and coding expectations, reducing confusion when changing the project.

How ghighi3f/garmin-grafana-mcp-server configures GitHub Copilot

Reuse

Borrowing it

Nothing to install: this file belongs to ghighi3f/garmin-grafana-mcp-server. 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/ghighi3f/garmin-grafana-mcp-server/main/.github/copilot-instructions.md

Clone the repo

git clone --depth 1 https://github.com/ghighi3f/garmin-grafana-mcp-server

Made for: GitHub Copilot.

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.

README.md

[![agentmods](https://agentmods.dev/badge/instructions/ghighi3f/garmin-grafana-mcp-server/copilot-instructions/github.svg)](https://agentmods.dev/instructions/ghighi3f/garmin-grafana-mcp-server/copilot-instructions)

Your own site

<a href="https://agentmods.dev/instructions/ghighi3f/garmin-grafana-mcp-server/copilot-instructions"><img src="https://agentmods.dev/badge/instructions/ghighi3f/garmin-grafana-mcp-server/copilot-instructions/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/instructions/ghighi3f/garmin-grafana-mcp-server/copilot-instructions"><img src="https://agentmods.dev/badge/instructions/ghighi3f/garmin-grafana-mcp-server/copilot-instructions.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 1,932 This file is loaded in full into every session.

When invoked 1,932 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.

Model	Per session	Once invoked
Fable 5.1	$0.01932	$0.01932
Opus 5.5	$0.00773	$0.00773
Sonnet 5.5	$0.00386	$0.00386
Haiku 4.5	$0.00193	$0.00193

Measured 2mo ago against content hash 19ae4d165a4e, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

garmin-grafana-mcp-server copilot-instructions.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 2mo 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.

.github/copilot-instructions.md · 148 lines

How it starts

The opening of the file, as written. The whole thing — 148 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Copilot Instructions — garmin-grafana-mcp-server

What this project is

This is a Model Context Protocol (MCP) server built with FastMCP in Python. It reads Garmin health and training data from a local InfluxDB instance (populated by garmin-grafana) and exposes it as MCP tools for LLM clients (Claude, Copilot, etc.) to consume.

The server is a pure data access layer — it never interprets data, never generates coaching advice, and never computes derived fitness metrics like ATL/CTL/TSB. The LLM is responsible for analysis.

Architecture

LLM Client  ──HTTP/SSE──▶  server.py (FastAPI + FastMCP)
                               │
                               ▼
                           influx.py (all queries)
                               │
                               ▼
                         InfluxDB (v1 or v2)
                       populated by garmin-grafana

server.py — FastAPI app, MCP tool registration, /health, startup banner.
influx.py — All InfluxDB connection logic and queries. Only file that touches the database.
utils.py — Shared helpers: pick(), safe_float(), safe_int(), iso_week_label(), week_start_from_label().
tools/ — Directory containing categorized tools (activity.py, load.py, recovery.py, detail.py, fitness.py, schema.py).

InfluxDB schema (garmin-grafana)

Measurements

Variable	Default value	Contains
`MEASUREMENT_ACTIVITIES`	`ActivitySummary`	Per-activity: distance, duration, HR, etc.
`MEASUREMENT_ACTIVITY_SESSION`	`ActivitySession`	Training effect, sub-sport
`MEASUREMENT_ACTIVITY_LAP`	`ActivityLap`	Per-lap splits: pace, HR, cadence, power
`MEASUREMENT_DAILY_STATS`	`DailyStats`	Body battery, stress, steps, resting HR
`MEASUREMENT_SLEEP_SUMMARY`	`SleepSummary`	Sleep score, stages, HRV, SpO2
`MEASUREMENT_RESTING_HR`	`DailyStats`	Resting heart rate field
`MEASUREMENT_HRV`	`HRV_Intraday`	HRV values (hrv5MinHigh)
`MEASUREMENT_VO2_MAX`	`VO2_Max`	VO2max running and cycling
`MEASUREMENT_RACE_PREDICTIONS`	`RacePredictions`	5K, 10K, half, marathon times
`MEASUREMENT_BODY_COMPOSITION`	`BodyComposition`	Weight

Read the full file on GitHub · 148 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.

2mo ago First seen · 148 lines · 1,932 tokens per session scan A 19ae4d165a4e

Subscribe to this mod's changes

garmin-grafana-mcp-server copilot-instructions.md is an instructions file published in the GitHub repository ghighi3f/garmin-grafana-mcp-server (11 stars, last pushed 4mo ago), licensed MIT. It adds 1,932 tokens to every session, about $0.0077 per session on Opus 5.5. 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.

Analytics and metrics ai-agents fastmcp garmin garmin-grafana grafana influxdb

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garmin-grafana-mcp-server: Instructions file for GitHub Copilot