smart-gym-mcp

smart-gym-mcp

Connects AI assistants to SmartGym on Mac, enabling users to review workouts, tweak routines, and build training programs in plain English, with changes syncing to iPhone and Apple Watch.

Category
Visit Server

README

smart-gym-mcp

Talk to your workouts. An MCP server that connects AI assistants like Claude to SmartGym on your Mac — so you can review your training, tweak routines, and build whole programs in plain English, and watch them sync to your iPhone and Apple Watch.

Why

SmartGym is a great workout tracker, but building and evolving a training program is still a lot of tapping. Meanwhile, AI assistants are genuinely good at programming workouts — they just had no way to reach your data.

This server bridges that gap. Your workout history, routines, and equipment become something you can have a conversation with:

  • "How has my bench press progressed over the last 3 months?"
  • "Add face pulls to my pull day, 3×12, after the rows."
  • "Build me a 3-day full-body comeback program based on what I was lifting in May, using only equipment I own."

Changes land in SmartGym itself — not a parallel app — so your data stays in one place and syncs everywhere via SmartGym's own engine.

What it can do

Read — health check, list routines, routine details, workout history, your equipment.

Write — create complete training programs, add / update / remove / reorder exercises, rename and edit routines. Every write is verified to sync across devices.

Safely — the server backs up the database before every write, only writes while the app is closed (it quits and relaunches SmartGym itself, which triggers sync), and refuses anything it can't do safely. Reads are strictly read-only.

Quick start

Requirements: macOS with SmartGym, Python ≥ 3.11, uv.

git clone https://github.com/sla1k/smart-gym-mcp
cd smart-gym-mcp
uv sync

Add it to your MCP client — e.g. Claude Code:

claude mcp add smartgym -- uv run --directory /path/to/smart-gym-mcp smartgym-mcp

or Claude Desktop (claude_desktop_config.json):

{
  "mcpServers": {
    "smartgym": {
      "command": "uv",
      "args": ["run", "--directory", "/path/to/smart-gym-mcp", "smartgym-mcp"]
    }
  }
}

Then ask your assistant to call smartgym_health — { ok: true, ... } means you're connected.

Configuration

Works out of the box with a standard SmartGym install. Env vars if you need them:

Var Default Purpose
SMARTGYM_DB_PATH SmartGym's container path database location
SMARTGYM_BACKUP_DIR ~/.smartgym-mcp/backups pre-write backups

Contributing

Issues and PRs welcome. Design notes live in DESIGN.md, ideas in FEATURES.md.

uv run pytest                                  # tests never touch your real data
uv run ruff check src tests && uv run mypy src

Disclaimer

This is an unofficial, personal project — not affiliated with or endorsed by the makers of SmartGym. It reads and writes the app's local database directly; use at your own risk and keep backups (the server makes one before every write).

License

MIT

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