Skip to main content
Glama
seselcuk
by seselcuk

Coach MCP — Experiment / Learning Project

This is not production. It is a side project created to experiment with the MCP (Model Context Protocol) version of the main Coach application. Goal: learn the MCP architecture, show what it would look like if integrated into the main project.

Architecture

mcp_servers/data/demo.db  (SQLite — uydurma seed veri)
        ↑                    ↑
   MCP server'lar        Streamlit
   (Claude Desktop)      (localhost:8501)

Key idea: One data source, two different clients — one conversational (Claude Desktop + MCP), one visual (Streamlit).

Related MCP server: fitness-mcp-server

Difference from the Main Project

Main Project (production)

This Experiment

Model access

Push model — Worker pastes context into prompt

Pull model — Claude pulls from MCP servers

Client

iOS + Streamlit

Claude Desktop + Streamlit

Deploy

Cloudflare Workers + D1

Local Python

Data source

Real Garmin API

Fake SQLite seed

Goal

Generate value for user

Learn/demonstrate architecture

MCP Servers

  1. garmin — Activity history, wellness, HR zone distribution, weekly load (from SQLite)

  2. pain — Pain history + log new pain (INSERT into SQLite)

  3. coach-rulescoach-principles.md + pain-rubric.md as prompt template

For details and API: mcp_servers/README.md

Quick Start

# 1. Bağımlılıklar
python3.11 -m venv .venv
.venv/bin/pip install -r requirements.txt

# 2. DB seed
.venv/bin/python -m mcp_servers.data.seed

# 3. Claude Desktop config kur
cp mcp_servers/claude_desktop_config.example.json \
   "$HOME/Library/Application Support/Claude/claude_desktop_config.json"

# 4. Claude Desktop'ı restart (Cmd+Q sonra yeniden aç)

# 5. Streamlit dashboard (opsiyonel, görsel demo için — port 8502, ana projenin 8501 ile çakışmaz)
.venv/bin/streamlit run streamlit_demo/app.py --server.port 8502

Demo Scenarios

For 3 scenarios and flow to be used in the presentation: DEMO.md

Folder Structure

antrenör_mcp/
├── mcp_servers/
│   ├── garmin/server.py       Aktivite + wellness + zone MCP
│   ├── pain/server.py         Ağrı geçmişi + log_pain tool
│   ├── coach_rules/server.py  Prensipler + rubric prompt template
│   ├── data/seed.py           DB seed script
│   ├── data/demo.db           SQLite (git'e girmez)
│   └── claude_desktop_config.example.json
├── streamlit_demo/app.py      3 tab dashboard
├── docs/
│   ├── coach-principles.md    Zone 2, shin, deload kuralları
│   └── pain-rubric.md         0-10 ağrı ölçeği
├── DEMO.md                    Sunum senaryosu
└── requirements.txt
A
license - permissive license
-
quality - not tested
C
maintenance

Maintenance

Maintainers
Response time
Release cycle
Releases (12mo)
Commit activity

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

Related MCP Servers

  • A
    license
    A
    quality
    A
    maintenance
    Enables Claude to access and query your Garmin Connect data, including sleep, activities, training load, and health metrics, through a set of read-only MCP tools.
    18
    1
    MIT
  • F
    license
    -
    quality
    D
    maintenance
    Provides MCP servers for Claude to access fitness data from Strava and intervals.icu, enabling natural language queries for activity analysis, advanced training metrics, and wellness tracking.
    1
  • F
    license
    -
    quality
    C
    maintenance
    Enables workout tracking and coaching within Claude conversations, managing exercise configs, logs, streaks, and health metrics via an MCP server with PostgreSQL.

View all related MCP servers

Related MCP Connectors

  • Garmin data in Claude & ChatGPT via the Garmin Health API. OAuth sign-in, no password sharing.

  • Garmin data in Claude: 135 tools — activities, sleep, HRV, training, workouts. Free, open source.

  • WHOOP recovery, strain, sleep and workouts in Claude via official WHOOP OAuth. Free, open source.

View all MCP Connectors

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/seselcuk/antrenor-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server