WorkoutGuide MCP
Allows importing health metrics from Apple Health for workout logging and tracking.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@WorkoutGuide MCPstart a new circuit training workout"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
WorkoutGuide MCP
A guided workout companion that lives entirely inside conversations with Claude. No app, no screen mid-workout — Claude is the coach, this MCP server is the memory (exercise config, per-attempt logs, streaks, health metrics from Apple Health / Whoop / manual entry).
Design truth: SPEC.md · State truth: HANDOFF.md · Coaching personality: skills/workout-coach.md
Layout
apps/mcp-server/ MCP server (Express + StreamableHTTP), Drizzle + Postgres
packages/shared/ zod schemas — source of truth for tool inputs & payloads
skills/ workout-coach.md coaching skillRelated MCP server: aiTrainer
Local dev
pnpm install
cp .env.example .env # fill in real values (openssl rand -hex 32 for secrets)
pnpm db:migrate # applies apps/mcp-server/drizzle/*.sql
pnpm dev # tsx watch
pnpm test # vitest: merge/streak units + full e2e vs in-process PostgresProduction (Replit)
Repl:
Claude-Workout-Guide— deploys from this repo via GitHub sync (repo is the source of truth, never edit on Replit directly).Add the built-in PostgreSQL database to the Repl (provides
DATABASE_URL).Replit Secrets (no
.envin prod):MCP_AUTH_TOKEN,MCP_PATH_SECRET(bothopenssl rand -hex 32), optionallyPORT(default 3000),LOG_LEVEL..replitbuilds with pnpm, runs migrations, and starts the server on a reserved VM (always-on, required for an MCP endpoint).
Connecting Claude
Client | URL | Auth |
claude.ai web / iOS connector |
| secret path (layer 1) |
Claude Code / API clients |
|
|
Both /api/mcp/… and bare /mcp/… mounts are served. Health check: GET /api/healthz (or /healthz). Rotate either secret in Replit Secrets → redeploy →
update the connector URL. Worst case: rotate, wipe DB, import_backup.
Schema notes (differences from SPEC §4)
exercise_logs.rest_started_at— added socheck_timecan measure an in-flight rest against the server clock.exercises.retired_at— exercises with logged history are retired (hidden, history preserved) instead of hard-deleted; template switches use this too.Backups carry a
looseLogsarray for attempts logged outside any session.v0.6 adds
ideas,plans,planned_sessions(SPEC §5c): training plans with a computed-status calendar, adherence scoring, and mid-run idea capture. 45 tools total. Client-facing usage lives in docs/claude-project-guide.md.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
No tool schema history has been recorded yet.
This server cannot be installed
Maintenance
Resources
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Looking for Admin?
If you are the server author, to access and configure the admin panel.
Related MCP Connectors
First strength app Claude can write to: plan training in chat, it lands in the app ready to log.
- SomviaOAuthapp.somvia
Private Apple Health metrics and workout detail for ChatGPT, Claude, and any MCP client.
Pace is a remote MCP server that exposes wearable and fitness data to Claude via the Model Context Protocol. It connects to Garmin, Oura, Whoop, Polar, Fitbit and 20+ devices and provides 15 tools for querying sleep, activity, recovery, and training data. Hosted on Google Cloud Run, OAuth 2.1 authentication, Streamable HTTP transport. Instructions: First you need to create an account at: https://pacetraining.co and connect your wearables. After that you can connect the remote Server via Custom Connector in Claude and OAuth 2.1 Flow startet.
Manage fitness coaching clients, workouts, programs, chats and funnels from your assistant.
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